U.S. patent application number 15/733176 was filed with the patent office on 2020-12-10 for implementation of orthogonal time frequency space modulation for wireless communications.
The applicant listed for this patent is Cohere Technologies, Inc.. Invention is credited to Shlomo Rakib, Seshadri Sathyanarayan.
Application Number | 20200389268 15/733176 |
Document ID | / |
Family ID | 1000005058584 |
Filed Date | 2020-12-10 |
![](/patent/app/20200389268/US20200389268A1-20201210-D00000.png)
![](/patent/app/20200389268/US20200389268A1-20201210-D00001.png)
![](/patent/app/20200389268/US20200389268A1-20201210-D00002.png)
![](/patent/app/20200389268/US20200389268A1-20201210-D00003.png)
![](/patent/app/20200389268/US20200389268A1-20201210-D00004.png)
![](/patent/app/20200389268/US20200389268A1-20201210-D00005.png)
![](/patent/app/20200389268/US20200389268A1-20201210-D00006.png)
![](/patent/app/20200389268/US20200389268A1-20201210-D00007.png)
![](/patent/app/20200389268/US20200389268A1-20201210-D00008.png)
![](/patent/app/20200389268/US20200389268A1-20201210-D00009.png)
![](/patent/app/20200389268/US20200389268A1-20201210-D00010.png)
View All Diagrams
United States Patent
Application |
20200389268 |
Kind Code |
A1 |
Sathyanarayan; Seshadri ; et
al. |
December 10, 2020 |
IMPLEMENTATION OF ORTHOGONAL TIME FREQUENCY SPACE MODULATION FOR
WIRELESS COMMUNICATIONS
Abstract
Device, methods and systems for implementing aspects of
orthogonal time frequency space (OTFS) modulation in wireless
systems are described. In an aspect, the device may include a
surface of an object for receiving an electromagnetic signal. The
surface may be structured to perform a non-electrical function for
the object. The surface may generate an electrical signal from an
electromagnetic signal. The electromagnetic signal may be received
from a transmitter. The transmitter may map digital data to a
digital amplitude modulation constellation in a time-frequency
space. The digital amplitude modulation constellation may be mapped
to a delay-Doppler domain and the transmitter may transmit to the
surface according to an orthogonal time frequency space modulation
signal scheme. The apparatus may further include a demodulator to
demodulate the electrical signal to determine digital data.
Inventors: |
Sathyanarayan; Seshadri;
(Santa Clara, CA) ; Rakib; Shlomo; (Santa Clara,
CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Cohere Technologies, Inc. |
Santa Clara |
CA |
US |
|
|
Family ID: |
1000005058584 |
Appl. No.: |
15/733176 |
Filed: |
December 4, 2018 |
PCT Filed: |
December 4, 2018 |
PCT NO: |
PCT/US2018/063818 |
371 Date: |
June 4, 2020 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
62594497 |
Dec 4, 2017 |
|
|
|
62594490 |
Dec 4, 2017 |
|
|
|
62620989 |
Jan 23, 2018 |
|
|
|
62621002 |
Jan 23, 2018 |
|
|
|
62622046 |
Jan 25, 2018 |
|
|
|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H04L 27/2602 20130101;
H04L 5/0007 20130101; H04L 5/0053 20130101; H04L 27/2647 20130101;
H04L 27/0008 20130101; H04L 27/206 20130101; H04B 1/385
20130101 |
International
Class: |
H04L 5/00 20060101
H04L005/00; H04L 27/00 20060101 H04L027/00; H04L 27/26 20060101
H04L027/26; H04L 27/20 20060101 H04L027/20; H04B 1/3827 20060101
H04B001/3827 |
Claims
1. An apparatus for wireless networking, comprising: a surface of
an object for receiving an electromagnetic signal, wherein the
surface is structured to perform a non-electrical function for the
object, wherein the electromagnetic signal was received from a
transmitter, wherein the transmitter mapped digital data to a
digital amplitude modulation constellation in a 2D time-frequency
domain, and wherein the digital amplitude modulation constellation
was mapped to a 2D delay-Doppler domain and transmitted to the
surface according to an orthogonal time frequency space (OTFS)
modulation signal scheme; and a demodulator to demodulate the
electrical signal to determine digital data.
2. The apparatus of claim 1, further comprising: a transmitter to
transmit, according to a short-range wireless standard, the
determined digital data.
3. The apparatus of claim 1, further comprising: a cellular
femto-cell transmitter to transmit the determined digital data
according to a cellular radio standard.
4. The apparatus of claim 3, wherein the cellular radio standard
includes one or more of a 3G standard, a 4G standard, a Long Term
Evolution standard, or a 5G standard.
5. The apparatus of claim 1, wherein the digital amplitude
modulation constellation is mapped to the 2D delay-Doppler domain
by transforming the digital amplitude modulation signal into a 2D
transformed orthogonal time frequency space signal using a 2D
Fourier transform from the 2D time-frequency domain to the 2D
delay-Doppler domain.
6. The apparatus of claim 1, wherein the digital amplitude
modulation constellation is quadrature amplitude modulation
(QAM).
7. The apparatus of claim 1, wherein the surface is a cellular
phone case, and wherein the wireless receiver apparatus is embedded
in the cellular phone case.
8. The of claim 1, wherein the surface is configured as a clothing
button.
9. The apparatus of claim 1, wherein the surface is an eyeglass
frame.
10. The apparatus of claim 1, wherein the surface is a lock.
11. A method of wireless networking reception, comprising:
generating, at a surface of an object, an electrical signal from an
electromagnetic signal, wherein the surface is structured to
perform a non-electrical function for the object, wherein the
electromagnetic signal was received from a transmitter, wherein the
transmitter mapped digital data to a digital amplitude modulation
constellation in a time-frequency space, and wherein the digital
amplitude modulation constellation was mapped to a delay-Doppler
domain and transmitted to the surface according to an orthogonal
time frequency space (OTFS) modulation signal scheme; and
demodulating the electrical signal to determine digital data.
12. The method of claim 11, further comprising: transmitting,
according to a short-range wireless standard, the determined
digital data.
13. The method of claim 11, further comprising: transmitting, by a
cellular femto-cell transmitter, the determined digital data
according to a cellular radio standard.
14-16. (canceled)
17. The method of claim 13, wherein the cellular radio standard
includes one or more of a 3G standard, a 4G standard, a Long Term
Evolution standard, or a 5G standard.
18. The method of claim 11, wherein the surface is a cellular phone
case, an eyeglass frame, a button, or a lock.
19. A device for wireless networking, comprising: a processor
configured to: generate an electrical signal from an
electromagnetic signal received at a surface of the device, wherein
the surface is structured to perform a non-electrical function for
the device, wherein the electromagnetic signal was received from a
transmitter, wherein the transmitter mapped digital data to a
digital amplitude modulation constellation in a time-frequency
space, and wherein the digital amplitude modulation constellation
was mapped to a delay-Doppler domain and transmitted to the surface
according to an orthogonal time frequency space (OTFS) modulation
signal scheme; and demodulate the electrical signal to determine
digital data.
20. The device of claim 19, further comprising: a transceiver
configured to transmit, according to a short-range wireless
standard, the determined digital data.
21. The device of claim 19, further comprising: a transceiver
configured to transmit, according to a cellular radio standard, the
determined digital data.
22. The device of claim 21, wherein the cellular radio standard
includes one or more of a 3G standard, a 4G standard, a Long Term
Evolution standard, or a 5G standard.
23. The device of claim 21, wherein the surface is a cellular phone
case, an eyeglass frame, a button, or a lock.
Description
CROSS-REFERENCES TO RELATED APPLICATIONS
[0001] This patent document claims priority to and benefits of U.S.
Provisional Application No. 62/594,497 entitled "ORTHOGONAL TIME
FREQUENCY SPACE MULTIPLEXING FOR WIRELESS NETWORKING" filed on 4
Dec. 2017, U.S. Provisional Application No. 62/594,490 entitled
"LIGHT BULB WITH INTEGRATED ANTENNA" filed on 4 Dec. 2017, U.S.
Provisional Application No. 62/620,989 entitled "VARIABLE FRAME
ASPECT RATIO AND DISCRETE FOURIER TRANSFORM PRECODING IN ORTHOGONAL
TIME FREQUENCY SPACE MODULATION" filed on 23 Jan. 2018, U.S.
Provisional Application No. 62/621,002 entitled "COMMUNICATION OF
ORTHOGONAL TIME FREQUENCY SPACE (OTFS) SYMBOLS WITHOUT CYCLIC
PREFIXES" filed on 23 Jan. 2018 and U.S. Provisional Application
No. 62/622,046 entitled "TRANSMITTER AND RECEIVER IMPLEMENTATION
FOR ORTHOGONAL TIME FREQUENCY SPACE MODULATED COMMUNICATIONS" filed
on 25 Jan. 2018. The entire contents of the aforementioned patent
applications are incorporated by reference as part of the
disclosure of this patent document.
TECHNICAL FIELD
[0002] The present document relates to wireless communication, and
more particularly, to implementation aspects of orthogonal time
frequency space (OTFS) modulation for wireless communications.
BACKGROUND
[0003] Due to an explosive growth in the number of wireless user
devices and the amount of wireless data that these devices can
generate or consume, current wireless communication networks are
fast running out of bandwidth to accommodate such a high growth in
data traffic and provide high quality of service to users.
[0004] Various efforts are underway in the telecommunication
industry to come up with next generation of wireless technologies
that can keep up with the demand on performance of wireless devices
and networks.
SUMMARY
[0005] This document discloses techniques that can be used to
implement orthogonal time frequency space (OTFS) modulation for
wireless communications.
[0006] In one example aspect, a wireless networking receiver
apparatus is disclosed. The apparatus may include a surface of an
object for receiving an electromagnetic signal. The surface may be
structured to perform a non-electrical function for the object. The
surface may generate an electrical signal from an electromagnetic
signal. The electromagnetic signal may be received from a
transmitter. The transmitter may map digital data to a digital
amplitude modulation constellation in a time-frequency space. The
digital amplitude modulation constellation may be mapped to a
delay-Doppler domain and the transmitter may transmit to the
surface according to an orthogonal time frequency space modulation
signal scheme. The apparatus may further include a demodulator to
demodulate the electrical signal to determine digital data.
[0007] In another example aspect, a light bulb apparatus is
disclosed. The light bulb may include one or more light sources.
The light bulb may further include a steerable directional antenna
coupled to the one or more light sources. The steerable directional
antenna may be further coupled to a transmitter. The transmitter
may map digital data to a digital amplitude modulation
constellation in a time-frequency space. The digital amplitude
modulation constellation may be mapped to a delay-Doppler domain
and transmitted to the steerable directional antenna according to
an OTFS modulation signal scheme.
[0008] In yet another example aspect, a method for wireless
communication with a variable frame aspect ratio in an OTFS system
includes allocating resources for wireless transmissions, wherein
the resources correspond to resource elements in one or more
two-dimensional transmission frames, wherein each transmission
frame comprises a first number of units along a delay dimension and
a second number of units along a Doppler dimension, and wherein an
aspect ratio of the transmission frame is variable over a time
period, and generating a waveform based on the allocated
resources.
[0009] In yet another example aspect, a method for wireless
communication with a variable frame aspect ratio in an OTFS system
includes receiving, at a user device, information associated with
resources allocated for wireless transmissions, wherein the
resources correspond to resource elements in one or more
two-dimensional transmission frames, wherein each transmission
frame comprises a first number of units along a delay dimension and
a second number of units along a Doppler dimension, and wherein an
aspect ratio of the transmission frame is variable over a time
period, and transmitting or receiving a waveform using the
information pertaining to the user device.
[0010] In yet another example aspect, a method for wireless
communication with a variable frame aspect ratio in an OTFS system
includes generating, from data bits, a signal for transmission
wherein the signal corresponds to an output of operations of
precoding by applying a Doppler dimension transform to the data
bits, thereby producing precoded data, mapping the precoded data to
transmission resources in one or more Doppler dimensions, along a
delay dimension, generating transformed data by transforming the
precoded data using an orthogonal time frequency space transform,
and converting the transformed data into a time domain waveform
corresponding to the signal.
[0011] In yet another example aspect, a method for wireless
communication with a variable frame aspect ratio in an OTFS system
includes converting a received time domain waveform into an
orthogonal time frequency space (OTFS) signal by performing an
inverse OTFS transform, extracting, from the OTFS signal, modulated
symbols along one or more Doppler dimensions, applying an inverse
precoding transform to the extracted modulated symbols, and
recovering data bits from an output of the inverse precoding
transform.
[0012] In yet another example aspect, a method for wireless
communication using an OTFS signal comprising one or more OTFS
frames in a two-dimensional delay-Doppler domain grid includes
generating a signal by concatenating OTFS symbols in a CP-less
(cyclic-prefix-less) manner, wherein in each OTFS frame in a
two-dimensional delay-Doppler domain grid, for at least some
Doppler domain values, a split allocation scheme is used for
assigning transmission resources along delay dimension, wherein the
split allocation scheme includes allocating a first portion to user
data symbols and a second portion to non-user data symbols, and
transmitting the signal over a wireless channel.
[0013] In yet another example aspect, a method for wireless
communication using an OTFS signal comprising one or more OTFS
frames in a two-dimensional delay-Doppler domain grid includes
partitioning resource elements of an OTFS frame into a first set
and a second set that include resource elements along a delay
dimension of the two-dimensional delay-Doppler domain grid, using
the first set of resource elements for non-user data symbols, using
the second set of resource elements to user data symbols, wherein
the second set of resource elements comprises lower-numbered delay
domain values, converting the OTFS frame to time-domain samples in
a non-cyclic-prefix manner, and generating a transmission waveform
of the OTFS signal comprising the time-domain samples.
[0014] In yet another example aspect, a method for wireless
communication using an OTFS signal comprising one or more OTFS
frames in a two-dimensional delay-Doppler domain grid includes
receiving the OFTS signal comprising time-domain samples,
converting the time-domain samples to an OTFS frame in a
non-cyclic-prefix manner, wherein resource elements of the OTFS
frame are partitioned into a first set and a second set that
include resource elements along a delay dimension of the
two-dimensional delay-Doppler domain grid, wherein the first set of
resource elements are used for non-user data symbols, wherein the
second set of resource elements are used for user data symbols,
wherein the second set of resource elements comprises
lower-numbered delay domain values, and performing channel
estimation or equalization based on the first set of resource
elements.
[0015] In yet another example aspect, a wireless communication
apparatus that implements the above-described methods is
disclosed.
[0016] In yet another example aspect, the method may be embodied as
processor-executable code and may be stored on a computer-readable
program medium.
[0017] These, and other, features are described in this
document.
DESCRIPTION OF THE DRAWINGS
[0018] Drawings described herein are used to provide a further
understanding and constitute a part of this application. Example
embodiments and illustrations thereof are used to explain the
technology rather than limiting its scope.
[0019] FIG. 1 shows an example of an OTFS transform.
[0020] FIG. 2 shows an example of an OTFS allocation in the
delay-spread and Doppler domain.
[0021] FIG. 3 shows another example of an OTFS allocation in the
delay-spread and Doppler domain, and mapping to the time-frequency
domain via the OTFS transform.
[0022] FIG. 4 shows an example of an OTFS allocation scheme in an
uplink.
[0023] FIGS. 5A and 5B show the packet error rate (PER) of OTFS and
SC-FDMA at equal PAPR in the rural macro channel and the urban
micro channel, respectively.
[0024] FIG. 6 shows an example of allocating UE resources along
delay dimensions, using one or more than one Doppler dimension.
[0025] FIG. 7 shows an example of assigning one or more physical
resource blocks (PRBs) along the Doppler dimension.
[0026] FIG. 8 shows examples of different variable aspect frame
ratios to accommodate low PAPR transmission of packets of
difference sizes along a single Doppler dimension.
[0027] FIGS. 9A and 9B show examples of DFT precoded OTFS for low
PAPR.
[0028] FIG. 10 shows an example of a transmitter and receiver block
diagram for an embodiment of the disclosed technology.
[0029] FIG. 11 shows an example of a transmitter and receiver block
diagram for another embodiment of the disclosed technology.
[0030] FIG. 12 shows an example of a transmitter and receiver block
diagram for yet another embodiment of the disclosed technology.
[0031] FIG. 13 shows an example of an OTFS delay-Doppler grid with
a guard grid region and a data symbol region.
[0032] FIGS. 14A, 14B and 14C shows examples of different guard
grid symbols.
[0033] FIG. 15 shows an example of an OTFS with different guard
grid sizes allocated to different transmissions.
[0034] FIG. 16 shows an example of an uplink OTFS frame with
different guard grid sizes allocated to different
transmissions.
[0035] FIG. 17 shows an example of a guard grid based OTFS
frame.
[0036] FIG. 18 shows an example of a transmitter and receiver block
diagram for yet another embodiment of the disclosed technology.
[0037] FIG. 19 depicts an example network configuration in which a
hub services for user equipment (UE).
[0038] FIG. 20 depicts an example embodiment in which an orthogonal
frequency division multiplexing access (OFDMA) scheme is used for
communication.
[0039] FIG. 21 illustrates the concept of precoding in an example
network configuration.
[0040] FIG. 22 is a spectral chart of an example of a wireless
communication channel.
[0041] FIG. 23 illustrates examples of downlink and uplink
transmission directions.
[0042] FIG. 24 illustrates spectral effects of an example of a
channel prediction operation.
[0043] FIG. 25 graphically illustrates operation of an example
implementation of a zero-forcing precoder (ZFP).
[0044] FIG. 26 graphically compares two implementations--a ZFP
implementation and regularized ZFP implementation (rZFP).
[0045] FIG. 27 shows components of an example embodiment of a
precoding system.
[0046] FIG. 28 is a block diagram depiction of an example of a
precoding system.
[0047] FIG. 29 shows an example of a quadrature amplitude
modulation (QAM) constellation.
[0048] FIG. 30 shows another example of QAM constellation.
[0049] FIG. 31 pictorially depicts an example of relationship
between delay-Doppler domain and time-frequency domain.
[0050] FIG. 32 is a spectral graph of an example of an
extrapolation process.
[0051] FIG. 33 is a spectral graph of another example of an
extrapolation process.
[0052] FIG. 34 compares spectra of a true and a predicted channel
in some precoding implementation embodiments.
[0053] FIG. 35 is a block diagram depiction of a process for
computing prediction filter and error covariance.
[0054] FIG. 36 is a block diagram illustrating an example of a
channel prediction process.
[0055] FIG. 37 is a graphical depiction of channel geometry of an
example wireless channel.
[0056] FIG. 38A is a graph showing an example of a precoding filter
antenna pattern.
[0057] FIG. 38B is a graph showing an example of an optical
pre-coding filter.
[0058] FIG. 39 is a block diagram showing an example process of
error correlation computation.
[0059] FIG. 40 is a block diagram showing an example process of
precoding filter estimation.
[0060] FIG. 41 is a block diagram showing an example process of
applying an optimal precoding filter.
[0061] FIG. 42 is a graph showing an example of a lattice and QAM
symbols.
[0062] FIG. 43 graphically illustrates effects of perturbation
examples.
[0063] FIG. 44 is a graph illustrating an example of hub
transmission.
[0064] FIG. 45 is a graph showing an example of the process of a UE
finding a closest coarse lattice point.
[0065] FIG. 46 is a graph showing an example process of UE
recovering a QPSK symbol by subtraction.
[0066] FIG. 47 depicts an example of a channel response.
[0067] FIG. 48 depicts an example of an error of channel
estimation.
[0068] FIG. 49 shows a comparison of energy distribution of an
example of QAM signals and an example of perturbed QAM signals.
[0069] FIG. 50 is a graphical depiction of a comparison of an
example error metric with an average perturbed QAM energy.
[0070] FIG. 51 is a block diagram illustrating an example process
of computing an error metric.
[0071] FIG. 52 is a block diagram illustrating an example process
of computing perturbation.
[0072] FIG. 53 is a block diagram illustrating an example of
application of a precoding filter.
[0073] FIG. 54 is a block diagram illustrating an example process
of UE removing the perturbation.
[0074] FIG. 55 is a block diagram illustrating an example spatial
Tomlinsim Harashima precoder (THP).
[0075] FIG. 56 is a spectral chart of the expected energy error for
different PAM vectors.
[0076] FIG. 57 is a plot illustrating an example result of a
spatial THP.
[0077] FIG. 58 shows examples of local signals in delay-Doppler
domain being non-local in time-frequency domain
[0078] FIG. 59 is a block diagram illustrating an example of the
computation of coarse perturbation using Cholesky factor.
[0079] FIG. 60 shows an exemplary estimate of the channel impulse
response for the SISO single carrier case.
[0080] FIG. 61 shows spectral plots of an example of the comparison
of Cholesky factor and its inverse.
[0081] FIG. 62 shows an example of an overlay of U.sup.-1 column
slices.
[0082] FIG. 63 is a block diagram illustrating an example of the
computation of coarse perturbation using U.sup.-1 for the SISO
single carrier case.
[0083] FIG. 64 is a block diagram illustrating an example of the
computation of coarse perturbations using W.sub.THP for the SISO
single carrier case.
[0084] FIG. 65 shows an exemplary plot of a channel frequency
response for the SISO single carrier case.
[0085] FIG. 66 shows an exemplary plot comparing linear and
non-linear precoders for the SISO single carrier case.
[0086] FIG. 67 is a block diagram illustrating an example of the
algorithm for the computation of perturbation using U.sup.-1 for
the SISO OTFS case.
[0087] FIG. 68 is a block diagram illustrating an example of the
update step of the algorithm for the computation of perturbation
using U.sup.-1 for the SISO OTFS case.
[0088] FIG. 69 shows an exemplary spectral plot of a channel
frequency response for the SISO OTFS case.
[0089] FIG. 70 shows exemplary spectral plots comparing the SINR
experienced by the UE for two precoding schemes for the SISO OTFS
case.
[0090] FIG. 71 is a block diagram illustrating an example of the
update step of the algorithm for the computation of perturbation
using U.sup.-1 for the MIMO single carrier case.
[0091] FIG. 72 is a block diagram illustrating an example of the
update step of the algorithm for the computation of perturbation
using W.sub.THP for the MIMO single carrier case.
[0092] FIG. 73 shows plots comparing the SINR experienced by the 8
UEs for two precoding schemes in the MIMO single carrier case.
[0093] FIG. 74 is a block diagram illustrating an example of the
update step of the algorithm for the computation of perturbation
using U.sup.-1 for the MIMO OTFS case.
[0094] FIG. 75 is a block diagram illustrating an example of the
update step of the algorithm for the computation of perturbation
using W.sub.THP for the MIMO OTFS case.
[0095] FIG. 76 shows plots comparing the SINR experienced by 1 UE
for two precoding schemes in the MIMO OTFS case.
[0096] FIG. 77 shows an exemplary modulation and demodulation
architecture for an OTFS modulated communication system.
[0097] FIG. 78 shows an exemplary modulation and demodulation
architecture for a DFT-S OTFS modulated communication system.
[0098] FIG. 79 shows an exemplary uplink base station turbo
receiver architecture.
[0099] FIG. 80 shows an exemplary downlink base station transmitter
architecture.
[0100] FIG. 81 shows an block diagram for exemplary downlink
channel processing at the base station.
[0101] FIG. 82 shows an example of uplink DFT-S OTFS user
multiplexing.
[0102] FIG. 83 shows an example of a fixed wireless access
system.
[0103] FIG. 84 shows yet another configuration of a fixed wireless
access system.
[0104] FIG. 85 shows an example of conversion of a signal between
the delay-Doppler domain and the time-frequency domain.
[0105] FIG. 86 shows an example of a time frequency grid on which
user data is assigned subgrids of resources.
[0106] FIG. 87 shows an example of a time frequency grid on which
user data is assigned to two subgrids of resources.
[0107] FIG. 88 shows an example of a time frequency grid on which
user data is assigned to three subgrids of resources.
[0108] FIG. 89 shows an example of a time frequency grid on which
user data is assigned to eight subgrids of resources.
[0109] FIG. 90 shows an example of a time frequency grid on which
user data is assigned to sixteen subgrids of resources.
[0110] FIG. 91 shows an example of time-frequency resource
assignment to four streams with 32 subsectors of transmission.
[0111] FIG. 92 shows an example of a beam pattern.
[0112] FIG. 93 shows an example of a dual polarization wide-band
antenna beam pattern.
[0113] FIG. 94 shows the beam pattern footprint of an example of a
24 azimuth.times.5 elevation antenna beam.
[0114] FIG. 95 shows an example of a 4 MIMO antenna beam
pattern.
[0115] FIG. 96 shows an example of an antenna deployment to achieve
full cell coverage using four quadrant transmissions.
[0116] FIG. 97 shows an example of an antenna deployment to achieve
full cell coverage using four quadrant transmissions in a 4 MIMO
system.
[0117] FIG. 98A illustrates an example embodiment of an
antenna.
[0118] FIG. 98B illustrates an example embodiment of an
antenna.
[0119] FIG. 98C illustrates an example embodiment of an
antenna.
[0120] FIG. 98D illustrates an example embodiment of an
antenna.
[0121] FIG. 99A shows an example of a cell tower configuration.
[0122] FIG. 99B shows an example of a cell tower configuration.
[0123] FIG. 99C shows an example of a cell tower configuration.
[0124] FIG. 100 shows an example of a system deployment in which
OTFS is used for wireless backhaul.
[0125] FIG. 101 shows another example of a system deployment in
which OTFS is used for wireless backhaul.
[0126] FIG. 102 shows an example deployment of an OTFS based fixed
wireless access system.
[0127] FIG. 103 shows an example of a lens antenna
configuration.
[0128] FIG. 104 shows example antenna configurations for
beamforming.
[0129] FIG. 105 shows an example of an antenna configuration in
which multiple antenna elements are used for multiple frequency
bands.
[0130] FIG. 106 shows an example of an antenna configuration in
which multiple antenna elements are used for transmission using
frequency stacking.
[0131] FIG. 107 shows an example of feed element configuration in
an antenna configuration.
[0132] FIG. 108 shows example feed element configurations in a
wideband antenna.
[0133] FIG. 109 illustrates different possible radial positioning
of antenna elements.
[0134] FIG. 110 depicts examples of beamforming to achieve a wider
and a narrower beamwidth pattern.
[0135] FIG. 111 shows an example of a variable beamwidth antenna
and a corresponding example radiation pattern.
[0136] FIG. 112 depicts an example of two communications networks,
in accordance with some example embodiments.
[0137] FIG. 113 depicts an example of an OTFS network, in
accordance with some example embodiments.
[0138] FIG. 114 depicts an example of an OTFS network and a wired
network, in accordance with some example embodiments.
[0139] FIG. 115 depicts examples of cases and enclosures that are
OTFS surfaces, in accordance with some example embodiments.
[0140] FIG. 116 depicts an example of a wireless system including
light bulbs with integrated antennas, in accordance with some
example embodiments.
[0141] FIG. 117 depicts an example of a light pole and an exploded
view of the top of the light pole including the light bulb, in
accordance with some example embodiments.
[0142] FIG. 118 depicts another example of a light pole with a
light bulb that includes an antenna for wireless communication, in
accordance with some example embodiments.
[0143] FIG. 119 depicts an example of a light pole with a light
bulb including an antenna and signal processing electronics, in
accordance with some example embodiments.
[0144] FIG. 120 depicts an example of a mast mounted antenna and an
example of a pole mounted antenna, in accordance with some example
embodiments.
[0145] FIG. 121 depicts an example of a tower mounted antenna and
another example of a pole mounted antenna, in accordance with some
example embodiments.
[0146] FIG. 122 depicts an example of a light pole, in accordance
with some example embodiments.
[0147] FIG. 123 is a flowchart of a wireless communication
method.
[0148] FIG. 124 is a flowchart of another wireless communication
method.
[0149] FIG. 125 is a flowchart of yet another wireless
communication method.
[0150] FIG. 126 is a flowchart of yet another wireless
communication method.
[0151] FIG. 127 is a flowchart of yet another wireless
communication method.
[0152] FIG. 128 is a flowchart of yet another wireless
communication method.
[0153] FIG. 129 is a flowchart of yet another wireless
communication method.
[0154] FIG. 130 is a flowchart of yet another wireless
communication method.
[0155] FIG. 131 is an example of a wireless communication
system.
[0156] FIG. 132 is a block diagram of a wireless communication
apparatus.
DETAILED DESCRIPTION
[0157] To make the purposes, technical solutions and advantages of
this disclosure more apparent, various embodiments are described in
detail below with reference to the drawings. Unless otherwise
noted, embodiments and features in embodiments of the present
document may be combined with each other.
[0158] Section headings are used in the present document, including
the appendices, to improve readability of the description and do
not in any way limit the discussion to the respective sections
only. The terms "hub" and user equipment/device are used to refer
to the transmitting side apparatus and the receiving side apparatus
of a transmission, and each may take the form of a base station, a
relay node, an access point, a small-cell access point, user
equipment, and so on.
[0159] The present document describes various implementation
aspects of OTFS modulation for wireless communications, and is
organized as follows: Section 1 provides an overview of OTFS
modulation, and Sections 2 and 3 discuss OTFS communication without
cyclic prefixes and using variable frame aspect ratios,
respectively. Section 4 covers OTFS multiple access and precoding,
and Section 5 covers transmitter and receiver implementations,
which may be used to implement OTFS modulated wireless
communications that are characterized by the features discussed in
Sections 2-5. Section 6 covers hardware and antenna implementations
that may be used in conjunction with the described transmitter and
receiver implementations, and include an antenna system comprising
a hemispherical dome (Section 6.1), a variable beamwidth multiband
antenna (Section 6.2), SWAP (size, weight and power) optimized
devices (Section 6.3), and light bulbs with integrated antennas
(Section 6.4). Methods related to embodiments of the presently
disclosed technology are described in Section 7.
Section 1: Overview of OTFS
1.1 OTFS Waveform Description
[0160] Traditional OFDM modulation operates in the frequency-time
domains. An OFDM resource elements (RE) occupies one subcarrier on
one particular OFDM symbol. In contrast, OTFS modulation operates
in the Delay spread-Doppler plane domains, which are related to
frequency and time by the symplectic Fourier transform, a
two-dimensional discrete Fourier transform. Similarly to
single-carrier frequency domain multiple access (SC-FDMA), OTFS can
be implemented as a preprocessing step on top of an underlying OFDM
signal. FIG. 1 illustrates the relationships between different
domains.
[0161] In OTFS, resource elements are defined in the delay-Doppler
domains, which provide a two-dimensional grid similar to OFDM. The
size of the delay-Doppler resource grid is related to the size of
the frequency-time plane by the signal properties, i.e. bandwidth,
frame duration, sub-carrier spacing, and symbol length. These
relationships are expressed by the following equalities:
N.sub..tau.=B/.DELTA.f
N.sub..nu.=TTI/T
[0162] where N.sub..tau. denotes the number of bins in the Delay
Spread domain and N.sub..nu. the number of bins in the Doppler
domain in the OTFS grid. B stands for the allocated bandwidth,
.DELTA.f is the subcarrier spacing, TTI is the frame duration
(transmit time interval), and T is the symbol duration. In this
example there is an exact matching between the delay spread and
frequency domains, and, similarly, between the Doppler and time
domains. Therefore, the number of delay dimensions equals the
number of active subcarriers in the OFDM signal, while the number
of Doppler dimensions equals the number of OFDM symbols in the
frame.
[0163] An OTFS Physical Resource Block (PRB) can be defined as the
number of symbols, also known as resource elements (RE)
corresponding to a minimum resource allocation unit, defined in the
Delay Spread-Doppler domain. For example, an OTFS PRB may be
defined as a region occupying N.sub.RB,.tau..times.N.sub.RB,.nu.
RE, where, the total number of RE is N.sub.RB=N.sub.RB,.tau.
N.sub.RB,.nu.. Different OTFS PRB configurations might be
considered. e.g. in one particular case a PRB may be defined to
span N.sub.RB,.tau..times.1 RE, i.e. this specific OTFS PRB
occupies a single Doppler dimension.
[0164] Conversion to Time-Domain Samples Denote the discrete OTFS
signal in the delay-Doppler plane by x(k,l), which corresponds to
the k.sup.th delay bin and l.sup.th Doppler bin. After the
symplectic transform, the following signal is obtained in the
frequency-time plane:
X [ m , n ] = 1 N .tau. N v k = 0 N .tau. - 1 l = 0 N v - 1 x [ k ,
l ] e - j 2 .pi. ( mk N .tau. - nl N v ) ##EQU00001##
Conversion to time domain samples can be executed in a number of
ways. In one embodiment, a conventional OFDM modulator is used to
convert each symbol X[m, 0], . . . , X[m, N.sub..nu.-1] to time
domain samples. As part of the OFDM modulation process, a cyclic
prefix may be added before the samples of each OFDM symbol. In
another embodiment, the OTFS signal is converted directly (i.e.
without intermediate conversion to time-frequency plane) to time
domain samples, by a single inverse Fourier Transform in the
Doppler domain. Time domain samples are obtained by direct
conversion as
s [ k + n N .tau. ] = 1 N v l = 0 N v - 1 x [ k , l ] e j 2 .pi. (
nl N v ) , k = 0 N .tau. - 1 , n = 0 N v - 1 ##EQU00002##
[0165] In this case, it is also possible to insert a cyclic prefix
between blocks of N.sub..tau. samples, consisting of the last
samples of the block. Alternatively, it is also possible to not
insert a cyclic prefix and use a Guard Grid instead.
[0166] OTFS Uplink Resource Allocation Scheme
[0167] UEs may be allocated to disjoint Doppler slices of the
delay-Doppler plane. An example is provided in FIG. 2. To modulate
data, UEs first place a sequence of QAM symbols on their assigned
resource elements, in the region of the delay-Doppler plane
corresponding to their PRB allocation. Next, the UEs perform an
OTFS tranform to convert their data from delay-Doppler domains to
time-frequency domains. Finally, the standard OFDM zero-padded IFFT
generates a time series. This process which takes place in the
transmitter can be seen in FIG. 3.
[0168] The proposed uplink scheme has, amongst other, at least two
key benefits: [0169] For small packets the PAPR of the time series
is low (equivalent to SC-FDMA). [0170] Packets can be spread across
all of time and frequency thus achieving the full diversity of the
channel yielding in higher reliability and enhanced link
margins.
[0171] Low PAPR OTFS Waveform
[0172] In a multiuser system, RE are generally assigned to
different users. When a user transmits, it fills the allocated RE
with QAM symbols and the rest of RE with zeros. It is easily shown
that OTFS may achieve very low PAPR if certain conditions are
satisfied with the allocation of RE. In particular, when a user is
allocated RE along a single Doppler dimension and on all delay
dimensions, the PAPR can be reduced by several dB in some
embodiment. DFT-spread OFDM signals are characterized by much lower
PAPR when compared to OFDM signals. More details and derivations
can be found in Appendix A1 of this document. Furthermore, when in
a DFT-spread OFDM signal, the size of the DFT preceding transform
equals the size of the subsequent inverse DFT in the OFDM
modulator, the PAPR of a pure single carrier modulation is
achieved.
[0173] In some embodiments, OTFS has low PAPR for small packets
sizes.
Assuming that a UE is allocated the first Doppler bin, then the
transmitted OTFS satisfies
x[k,l]=0,.A-inverted.k.noteq.0
[0174] As a result, the signal after the symplectic transform
simplifies to
X [ n , m ] = 1 N S , .tau. N S , v l = 0 N S , .tau. - 1 x [ 0 , l
] e - j 2 .pi. ( m l N S , .tau. ) ##EQU00003##
[0175] Therefore, for any OFDM symbol n within the TTI, the signal
in the frequency domain is the result of applying a DFT to the
delay domain symbols, which is equivalent to the operation done by
SC-FDMA. As a result, for symbol n, the OTFS waveform is equivalent
to a DFT-spread waveform (i.e. SC-FDMA), multiplied by a constant
phase, which for this example is 0. Therefore, in terms of PAPR,
OTFS also enjoys the benefits observed in SC-FDMA.
[0176] Overhead in OTFS
[0177] A significant source of overhead in OTFS stems from the
insertion of a cyclic prefix between the underlying OFDM symbols,
or blocks of N.sub..tau. samples. As an example, in LTE the
overhead may be as high as 7%, or more if an extended cyclic prefix
is used. This document discloses an overhead reduction technique,
which reduces the overhead compared to a system using a cyclic
prefix.
[0178] Frequency Diversity
[0179] The OTFS modulation can spread each QAM symbol into
different bandwidths (even over the full bandwidth) and TTI
durations. Typically this spreading in frequency and time is larger
than the one of OFDM and so often achieves the full diversity of
the channel. In contrast, for small packets, SC-FDMA only transmits
over a narrow bandwidth. The concept is illustrated in FIG. 4.
[0180] SC-FDMA cannot spread their allocation across frequency
without always paying a penalty in pilot overhead (for the case of
evenly spreading data across frequency) or increasing PAPR (for the
case of unevenly spreading across frequency), whilst these effects
can eventually be avoided by OTFS.
[0181] While both OTFS and SC-FDMA keep the PAPR at low levels,
OTFS inherent frequency and time diversity extraction and the lack
of such in SC-FDMA translates to performance superiority expressed
as enhanced link budget and higher reliability of payload
delivery.
[0182] Simulation Results
[0183] The evaluation of the packet error rate (PER) of OTFS and
SC-FDMA under the simulation assumptions are reported in Table
1.
TABLE-US-00001 TABLE 1 Evaluation Assumptions Parameter Value
Carrier frequency 4 GHz System BW 10 MHz TTI length 1 msec
Subcarrier spacing 15 kHz Transport Block Size 3 PRB Coding LTE
Turbo code MCS 16-QAM, R = 1/2; 64-QAM, R = 1/2 Antenna
Configuration SISO Receiver Turbo equalizer (both OTFS and SC-FDMA)
Channel profile Rural Macro (RMa), Urban Micro (UMi) UE Speed 30
kph Channel estimation Ideal
[0184] A potential cell edge situation, with a small Transport
Block size of 3 PRB, was considered. Both UMi and RMa channel
models were simulated, with a UE speed of 30 kph (since the
resilience of OTFS to higher Doppler was previously reported, in
these simulations higher UE speeds are omitted). For a fair
comparison, both OTFS and SC-FDMA were evaluated using an advanced
turbo equalizer receiver. The effect of channel estimation was not
accounted for, being the simulation carried out with perfect
channel knowledge at the receiver. Results, shown in FIG. 5A and
FIG. 5B, confirm that the higher degree of diversity attained by
OTFS results in remarkable performance advantages. Gains for a 10%
target PER are summarized in Table 2.
TABLE-US-00002 TABLE 2 Performance Gain of OTFS Over SC-FDMA RMa
UMi 16-QAM 2.3 dB 4.2 dB 64-QAM 2.5 dB 3.7 dB
1.2 Low OTFS PAPR Based on Adjustable Frame Aspect Ratio
Definitions
[0185] An OTFS frame may be defined as a set of RE arranged along
delay and Doppler dimensions. In a rectangular arrangement, the
OTFS frame is characterized by N.sub..tau. delay dimensions and by
N.sub..nu. Doppler dimensions, resulting in a total of
N.sub.SF=N.sub..tau..times.N.sub..nu. RE. The relation between
N.sub..tau. and N.sub..nu., while keeping the product fixed, is
defined as the frame aspect ratio. The total of RE within a frame
is divided into one or more sets, and allocated to one or more
users.
[0186] In one embodiment of the disclosed technology, each UE is
allocated resources along delay dimensions first (as shown in FIG.
6). When all delay dimensions of a given Doppler dimension are
used, additional delay dimensions in the next Doppler dimension are
used, until all resources are allocated. This type of resource
allocation is described as Delay first symbol mapping.
[0187] In one embodiment, resources are organized in physical
resource blocks (PRB), containing a fixed number of symbols. PRB
are defined along one Doppler dimension. Each Doppler dimension may
contain one or more PRB. An illustration is provided in FIG. 7.
[0188] The number of symbols in one PRB may vary due to the
insertion of reference symbols, control signaling, blank symbols,
or other aspects necessary for the transmission.
[0189] In another embodiment, no PRB are defined, and allocations
are performed with Delay first mapping for an arbitrary number of
symbols.
[0190] Adjustable Frame Aspect Ratio
[0191] In this section, techniques to achieve low PAPR OTFS signals
in a system with varying number of users and packet sizes are
described. In particular, techniques based on changing the aspect
ratio of the OTFS frame are disclosed.
[0192] In one embodiment, for a given PRB size N.sub.PRB defined
along one Doppler dimension, the frame aspect ratio is adjusted so
that N.sub..tau. equals (or is a multiple of) N.sub.PRB, and
N.sub..tau. is adjusted dynamically. Correspondingly, N.sub..nu. is
also adjusted to maintain N.sub.SF constant. Using this approach,
users with a packet size equal to one PRB may be transmitted with
minimum PAPR using a frame aspect ratio such that
N.sub..tau.=N.sub.PRB. Moreover, users with a packet size equal to
k PRB may be transmitted with minimum PAPR using a frame aspect
ratio such that N.sub..tau.=kN.sub.PRB. An illustration of this
embodiment is provided in FIG. 8. The embodiment also includes
other values for N.sub..tau., N.sub..nu., and N.sub.PRB as well as
other aspect ratio variations than those portrayed in the
figure.
[0193] After the OTFS frame has been conformed, conversion to time
domain samples is carried out. In one embodiment, conversion to
time domain consists of two steps: a first step is a 2-dimensional
Fourier transform to convert the signal to the time-frequency
domains, and a second step consists of an OFDM modulator, which
converts the signal to the time domain by means of an additional
Fourier transform, and prepends a cyclic prefix to every OFDM
symbol. In this method, OFDM dimensions (number of sub-carriers and
number of symbols per frame) are adjusted to match the OTFS grid
size, based on the previously described equalities. In another
embodiment, conversion to time domain consists of a single step
consisting of a Fourier transform to convert from Doppler to time
domains, as detailed previously.
[0194] Frame Aspect Ratio Configuration
[0195] The frame aspect ratio is configured by the Base Station and
indicated to the UE prior to transmission.
[0196] One or more of the following procedures are used when
variable frame aspect ratio is used in the uplink:
[0197] (1) Communication by means of the downlink control channel:
in an earlier OTFS downlink frame the downlink control channel
contains information regarding the aspect ratio of an upcoming
uplink frame. This information is contained in a downlink control
information message part of the common control channel, to be
received by all UEs. Alternatively, this information is contained
in the UE-specific downlink control channel. Aspect ratio
indication may be for a single OTFS frame, or for multiple OTFS
frames. The aspect ratio of the downlink control region (common or
UE-specific) is known to the UE. For example, it is determined by
upper layer signaling or system configuration.
[0198] (2) Communication by means of UE configuration or upper
layer signaling: the UE is configured for a given frame aspect
ratio. Configuration occurs by means of upper layer configuration
messages, either when activating the UE or when initiating a
transmission. Configuration may change semi-statically, that is, in
a time frame significantly larger than an OTFS frame period.
[0199] (3) Implicit indication: a UE is required to infer the frame
aspect ratio from other information appearing in the control
channel, as well as the system state. For example, it is required
to infer the aspect ratio from the uplink scheduling assignment and
its configuration. In one embodiment, a UE configured as low PAPR
assumes that the frame aspect ratio is such that its assigned
resources fit in exactly one Doppler dimension when using all delay
dimensions.
[0200] (4) UE detection: a UE may be required to detect the
downlink frame aspect ratio based on the physical characteristics
of the transmitted signal, and derive the corresponding uplink
frame aspect ratio using a predetermined algorithm. For example, it
may be assumed that the same aspect ratio is used for uplink and
downlink. It may also be assumed that the uplink aspect ratio has a
fixed relation to the downlink aspect ratio. This fixed relation
may be given by the desired uplink/downlink traffic ratio in the
system.
[0201] For the downlink, one or more of the following procedures
are used: [0202] (1) Communication by means of the downlink control
channel: in an earlier OTFS downlink frame the downlink control
channel contains information regarding the aspect ratio of an
upcoming uplink frame. This information is contained in a downlink
control information message part of the common control channel, to
be received by all UEs. Alternatively, this information is
contained in the UE-specific downlink control channel. Aspect ratio
indication may be for a single OTFS frame, or for multiple OTFS
frames. The aspect ratio of the downlink control region (common or
UE-specific) is known to the UE. For example, it is determined by
upper layer signaling or system configuration. [0203] (2)
Communication by means of UE configuration or upper layer
signaling: the UE is configured for a given frame aspect ratio.
Configuration occurs by means of upper layer configuration
messages, either when activating the UE or when initiating a
transmission. Configuration may change semi-statically, that is, in
a time frame significantly larger than an OTFS frame period. [0204]
(3) Implicit detection: a UE may be required to infer the frame
aspect ratio from other information appearing in the control
channel, as well as the system state. For example, it be required
to infer the aspect ratio from the downlink scheduling assignment
and its configuration. [0205] (4) UE detection: a UE may be
required to detect the frame aspect ratio based on the physical
characteristics of the transmitted signal.
[0206] For OTFS over OFDM, changing the aspect ratio of the OTFS
frame implies a change in the aspect ratio of the OFDM frame, since
there is a 1-to-1 correspondence between the number of Delay
dimensions in OTFS and number of subcarriers in OFDM, and also
between the number of Doppler dimensions in OTFS and the number of
symbols in the corresponding OFDM frame. For the corresponding OFDM
frame, the following parameters are adapted to the OTFS frame
aspect ratio: [0207] An OFDM frame numerology is defined for every
aspect ratio of the OTFS frame, where numerology comprises
subcarrier spacing, number of sub-carriers, number of symbols,
symbol duration and cyclic prefix duration. [0208] Reference
signals are defined specifically for every supported aspect ratio.
The criterion used to adapt reference signals is to maintain
overhead ratio constant, as well as to maintain a constant
separation in both time and frequency domains between reference
signals, if possible. [0209] Resource mapping, as described by
control messages, is adapted to the aspect ratio.
1.3 Low PAPR OTFS Based on DFT Precoded OTFS
[0210] In this section, techniques to achieve low PAPR OTFS signals
in a system with varying number of users and packet sizes are
described. In particular, techniques based on applying DFT
precoding prior to the OTFS transform are disclosed.
[0211] In one embodiment, a Doppler domain discrete Fourier
transform (DFT) precoding is applied prior to the OTFS transform.
The size of the Doppler domain DFT precoding transform ranges
between 1 and N.sub..nu.. The output is then mapped onto the
corresponding number of Doppler dimensions. As a result, low PAPR
transmission is achieved for any size of the DFT precoding
transform. An illustration of this technique is provided in FIGS.
9A and 9B.
[0212] A user with packet size equal to one PRB transmits using a
DFT precoding transform of size 1, and the output is mapped to
N.sub..tau. delay dimensions and one Doppler dimension. A user with
packet size equal to L PRB transmits using a DFT precoding
transform of size L, and the output is mapped to N.sub..tau. delay
dimensions and L Doppler dimensions. Mathematically, the DFT
precoding step can be expressed as follows. Let x(k,l) denote QAM
symbols corresponding to the data to be transmitted (which may be
encoded using a channel code), arranged in a matrix with
N.sub..tau. rows and L columns. A DFT is performed along rows,
resulting in
x ^ ( k , l ' ) = 1 L l = 0 L - 1 x ( k , l ) e - j 2 .pi. ll ' L ,
l ' = 0 L - 1 ##EQU00004##
{circumflex over (x)}(k,l') is Then mapped onto L columns (Doppler
dimensions) in the OTFS grid of size N.sub..tau..times.N.sub..nu..
Different users are mapped onto disjoint sets of Doppler
dimensions. The following options are possible for mapping to
Doppler dimensions: [0213] 1. Map to an adjacent set of L Doppler
dimensions. [0214] 2. Map in an interleaved fashion, where the
total of N.sub..nu. Doppler dimensions is divided into an integer
number of blocks of size M, and the i.sup.th Doppler dimension in
each block is selected. [0215] 3. Other mappings
[0216] After mapping to the OTFS frame, conversion to time domain
samples is carried out. In one embodiment, conversion to time
domain consists of two steps: a first step is a 2-dimensional
Fourier transform to convert the signal to the time-frequency
domains, and a second step consists of an OFDM modulator, which
converts the signal to the time domain by means of an additional
Fourier transform, and prepends a cyclic prefix to every OFDM
symbol.
[0217] Block diagrams for the transmitter and receiver structures
are shown in FIG. 10. Note that in a similar embodiment reference
signal (RS) insertion may also occur before the OTFS transform. For
the receiver, two different embodiments are considered (shown in
the block diagrams below). One corresponds to a single user
receiver, where only symbols for one user are recovered. A second
one corresponds to a multi-user receiver, where symbols from all
users are recovered. In the multi-user receiver, the Doppler IDFT
block is executed for every user in the OTFS frame. In a different
embodiment, equalization is performed in the frequency domain, as
illustrated in FIG. 11.
[0218] In another embodiment, conversion to time domain consists of
a single step consisting of a Fourier transform to convert from
Doppler to time domains. A block diagram description is provided in
FIG. 12.
[0219] The proposed embodiment may lead to a reduction of the peak
to average power ratio (PAPR) of the transmitted signal of several
dB. In embodiment 1). For example, when a localized mapping of the
Doppler dimensions is used, the original data symbols may be
interpreted as residing in the time-delay domains. The combination
of size L DFT and size N.sub..nu. IDFT, combined with mapping on
adjacent subcarriers, may be interpreted as a time domain
interpolator (the operation consisting of conversion by means of
DFT, zero padding, and conversion back by means of IDFT is an
interpolator). Therefore, the resulting samples of DFT-precoded
OTFS are in fact samples of a single carrier signal interpolated by
a factor N.sub..nu./L.
[0220] In embodiment 2), i.e. when interleaved mapping of the
Doppler dimensions is used, the original data symbols may be
interpreted as residing in the time-delay domains. The combination
of L DFT and size N.sub..nu. IDFT, combined with mapping every M-th
subcarrier, leads to the repetition, by a factor of M, of the
original samples, where each repetition is multiplied by a linear
phase. Therefore, the resulting samples of DFT-precoded OTFS are in
fact samples of a single carrier signal repeated by a factor
M=N.sub..nu./L.
1.4 OTFS Modulation with Guard Grid
[0221] In this section, aspects related to Guard Grid Based OTFS
(GG-OTFS), which is a form of OTFS that does not require the use of
a cyclic prefix between symbols, are described.
[0222] In this embodiment, OTFS blocks of N.sub..tau. samples are
concatenated without insertion of any cyclic prefix. In the OTFS
Delay-Doppler grid, special symbols, which may be known to the OTFS
receiver, are allocated to the last N.sub.G Delay dimensions on
every Doppler dimension. This region is denoted as the
N.sub.G.times.N.sub..nu. Guard Grid. Such a system may be referred
to as Guard Grid based OTFS or GG-OTFS.
[0223] FIG. 13 illustrates this embodiment in the Delay-Doppler
domain plane.
[0224] Regarding the Guard Grid, the following embodiments are
possible: [0225] (1) Zero values (blank symbols) are allocated to
all symbols in the Guard Grid. By using this procedure, a circulant
channel may be observed by symbols in the rest of the Delay-Doppler
grid. This facilitates equalization, permitting the use of
techniques similar to those used in cyclic prefix based OTFS.
[0226] (2) Non-zero values are allocated to symbols in the first
Doppler dimension of the Guard Grid, while zero values (blank
symbols) are allocated in other dimensions. By using this
procedure, a circulant channel may be observed by symbols in the
rest of the Delay-Doppler grid. This facilitates equalization,
permitting the use of techniques similar to those used in cyclic
prefix based OTFS. [0227] (3) The first data samples of the data
grid are copied as the samples of the Guard Grid. By using this
procedure, a circulant channel may be observed by symbols in the
rest of the Delay-Doppler grid. This facilitates equalization,
permitting the use of techniques similar to those used in cyclic
prefix based OTFS. [0228] (4) Non-zero values are allocated on all
symbols in the Guard Grid. [0229] (5) In embodiments 2 and 4,
special symbols used for channel estimation by the receiver are
allocated to one or more Delay-Doppler dimensions of the Guard
Grid. These symbols may be specific to every transmitter, either
user or base station. These symbols may be inferred by the receiver
based on an identifier associated with the transmitter, such as
cell ID or beam ID.
[0230] FIGS. 14A, 14B and 14C illustrate embodiments 1-5 for Guard
Grid design.
[0231] On any of these embodiments, the size of the Guard Grid may
be fixed system-wide, or variable. By variable, the following
options are described: [0232] Guard Grid Size may be determined
upon system deployment, and fixed for every transmitter in the
system. An equal value for all, or different values per transmitter
may be determined. [0233] Guard Grid Size may be determined upon
the establishment of a connection, and fixed throughout the
connection at a value specific for that connection. [0234] Guard
Grid Size may vary dynamically, depending on propagation conditions
or other system aspects. [0235] A combination of the above options
may be used.
[0236] FIG. 15 provides an illustration of an OTFS frame with
different Guard Grid size for different transmissions corresponding
to different users.
[0237] In the specific case of uplink transmission, the uplink
frame at the receiver originates from different transmitters, as
illustrated in FIG. 16.
[0238] By varying the size of the Guard Grid, it may be possible to
reduce the amount of overhead with respect to a fixed Guard Grid
design, which must support worst-case scenarios and possibly be
unnecessarily large for most typical cases. For the same reason, it
may also be possible to reduce the overhead of cyclic prefix based
OTFS.
[0239] FIG. 17 illustrates Guard Grid Based OTFS embodiment in the
time domain, after the OTFS transform. Time domain samples
corresponding to the Guard Grid (in green) are obtained through
processing of the Guard Grid symbols in the Delay-Doppler grid by
means of the OTFS transform. In addition, initial Guard samples are
added, preceding the OTFS frame samples, in order to avoid
interference between OTFS frames. In one embodiment, Initial Guard
samples are identical to the time domain samples resulting from the
OTFS transform of the Guard Grid samples.
[0240] The transmitter for GG-OTFS consists of at least the
following blocks: [0241] Data pre-processing (including
segmentation) [0242] Forward error correction (FEC) encoding [0243]
Symbol mapper [0244] Reference signal insertion [0245] Guard Grid
insertion [0246] OTFS transform [0247] Initial Guard Samples
insertion
[0248] The receiver for GG-OTFS consists of at least the following
blocks: [0249] Initial Guard Samples removal [0250] OTFS inverse
transform [0251] RS extraction and channel estimation [0252] Guard
Grid removal [0253] Equalizer [0254] Symbol demapper [0255] FEC
decoding [0256] Data post-processing (including aggregation)
[0257] It is also possible to use iterative (or Turbo) receivers
for GG-OTFS. In that case, a symbol mapper and an OTFS transform
blocks would also be part of the receiver.
[0258] Transmitter and receiver block diagrams are depicted in FIG.
18.
[0259] Signaling and System Aspects
[0260] In this section, system procedures related to using the
Guard Grid in lieu of cyclic prefixes, and which may be implemented
by the disclosed technology, are described.
[0261] Guard Grid Configuration
[0262] The Guard Grid is configured by the Base Station and
indicated to the UE prior to transmission. The following aspects
may be configured regarding the Guard Grid: [0263] Size, in number
of Delay dimensions used [0264] Contents of the Guard Grid
symbols
[0265] When the Guard Grid is configured dynamically, one or more
of the following procedures are used: [0266] (1) Communication by
means of the downlink control channel: in an earlier or the current
downlink frame, the downlink control channel contains Guard Grid
configuration information. This information is contained in a
downlink control information message part of the common control
channel, to be received by all UEs. Alternatively, this information
is contained in the UE-specific downlink control channel. The Guard
Grid configuration may be for a single frame, or for multiple
frames. The Guard Grid configuration of the control region (common
or UE-specific) is known to the UE as determined by upper layer
signaling. [0267] (2) Communication by means of UE configuration or
upper layer signaling. Configuration occurs by means of upper layer
configuration messages, either when activating the UE or when
initiating a transmission. Configuration may change
semi-statically, that is, in a time frame significantly larger than
an OTFS frame period. [0268] (3) Implicit detection: a UE may be
required to infer the Guard Grid configuration from other
information appearing in the control channel, as well as the system
state. [0269] (4) UE detection: a UE may be required to detect the
Guard Grid configuration based on the physical characteristics of
the transmitted signal.
[0270] The Guard Grid configuration for downlink and uplink
transmissions of a given UE may be predetermined in advance. For
example, indication of a given Guard Grid configuration for the
downlink may imply a given Guard Grid configuration for the uplink.
Uplink and downlink configurations may be identical or related by a
mathematical or pre-established relation.
Section 2: OTFS Communication without Cyclic Prefixes
[0271] In orthogonal frequency division multiplexing (OFDM) and
similar systems, cyclic prefix (CP) are used for improving
performance of digital communication. A significant source of
overhead stems from the insertion of a CP between the underlying
OFDM symbols. As an example, in LTE the overhead can be as high as
7%, or more if an extended cyclic prefix is used. The techniques
disclosed in the present document can be used to achieve overhead
reduction, which reduces the overhead compared to a system using a
cyclic prefix. As such, the disclosed techniques perform
transmission resource allocation such that OTFS transmissions can
be made without using CP, for example by concatenating symbols
without any intervening CPs.
[0272] Some additional embodiments for OTFS communication without
cyclic prefixes are described in Section 1.4, and others are
described in Section 7.
Section 3: Variable Frame Aspect Ratios in OTFS
[0273] In some embodiments, the aspect ratio of the transmission
frame (e.g., the ratio of number of delay units and number of
dimension units) may be changed over a period of time. This change
may be performed to accommodate user data packet size changes. In
an example, the aspect ratio may be changed such that one user
device packet maps to one PRB in the delay-Doppler grid. Various
methods may be used for signaling the change from a transmitting
device (or a device that controls resource scheduling) to a
receiving device. The signaling may be performed sufficiently in
advance (e.g., 1 millisecond, or one transmit time interval TTI) so
that the receiving device may adapt its PHY and MAC for the change
in the aspect ratio.
[0274] In some embodiments, the signaling may be performed using
one or more of the following techniques: a) downlink control
channel signaling, (b) upper layer signaling, (c) implicit
indication, or (d) signal detection. Furthermore, the signaling may
include signaling of various transmission parameters such as one or
more of subcarrier spacing, a number of sub-carriers in the
transmission frames, a number of symbols in the transmission
frames, symbol duration and cyclic prefix duration. Similar
signaling techniques may be used for future transmissions in both
downlink and uplink directions.
[0275] In some embodiments, the aspect ratio selection may be
performed such that the frame area (delay domain.times.Doppler
domain units) may be kept constant. Alternatively, the frame area
(total number of resource elements in the frame) may be changed to
adapt the communication system to different channels.
[0276] Some additional embodiments for OTFS communication using
variables frame aspect ratios are described in Section 1.2, and
others are described in Section 7.
Section 4: Multiple Access and Precoding in OTFS
[0277] FIG. 19 depicts a typical example scenario in wireless
communication is a hub transmitting data over a fixed time and
bandwidth to several user devices (UEs). For example: a tower
transmitting data to several cell phones, or a Wi-Fi router
transmitting data to several devices. Such scenarios are called
multiple access scenarios.
[0278] Orthogonal Multiple Access
[0279] Currently the common technique used for multiple access is
orthogonal multiple access. This means that the hub breaks it's
time and frequency resources into disjoint pieces and assigns them
to the UEs. An example is shown in FIG. 20, where four UEs (UE1,
UE2, UE3 and UE4) get four different frequency allocations and
therefore signals are orthogonal to each other.
[0280] The advantage of orthogonal multiple access is that each UE
experience its own private channel with no interference. The
disadvantage is that each UE is only assigned a fraction of the
available resource and so typically has a low data rate compared to
non-orthogonal cases.
[0281] Precoding Multiple Access
[0282] Recently, a more advanced technique, precoding, has been
proposed for multiple access. In precoding, the hub is equipped
with multiple antennas. The hub uses the multiple antennas to
create separate beams which it then uses to transmit data over the
entire bandwidth to the UEs. An example is depicted in FIG. 21,
which shows that the hub is able to form individual beams of
directed RF energy to UEs based on their positions.
[0283] The advantage of precoding it that each UE receives data
over the entire bandwidth, thus giving high data rates. The
disadvantage of precoding is the complexity of implementation.
Also, due to power constraints and noisy channel estimates the hub
cannot create perfectly disjoint beams, so the UEs will experience
some level of residual interference.
[0284] Introduction to Precoding
[0285] Precoding may be implemented in four steps: channel
acquisition, channel extrapolation, filter construction, filter
application.
[0286] Channel acquisition: To perform precoding, the hub
determines how wireless signals are distorted as they travel from
the hub to the UEs. The distortion can be represented
mathematically as a matrix: taking as input the signal transmitted
from the hubs antennas and giving as output the signal received by
the UEs, this matrix is called the wireless channel.
[0287] Channel prediction: In practice, the hub first acquires the
channel at fixed times denoted by s.sub.1, s.sub.2, . . . ,
s.sub.n. Based on these values, the hub then predicts what the
channel will be at some future times when the pre-coded data will
be transmitted, we denote these times denoted by t.sub.1, t.sub.2,
. . . , t.sub.m.
[0288] Filter construction: The hub uses the channel predicted at
t.sub.1, t.sub.2, . . . , t.sub.m to construct precoding filters
which minimize the energy of interference and noise the UEs
receive.
[0289] Filter application: The hub applies the precoding filters to
the data it wants the UEs to receive.
[0290] Channel Acquisition
[0291] This section gives a brief overview of the precise
mathematical model and notation used to describe the channel.
[0292] Time and frequency bins: the hub transmits data to the UEs
on a fixed allocation of time and frequency. This document denotes
the number of frequency bins in the allocation by N.sub.f and the
number of time bins in the allocation by N.sub.t.
[0293] Number of antennas: the number of antennas at the hub is
denoted by L.sub.h, the total number of UE antennas is denoted by
L.sub.u.
[0294] Transmit signal: for each time and frequency bin the hub
transmits a signal which we denote by .phi.(f,t).di-elect
cons..sup.L.sup.h for f=1, . . . , N.sub.f and t=1, . . . ,
N.sub.t.
[0295] Receive signal: for each time and frequency bin the UEs
receive a signal which we denote by y(f,t).di-elect
cons..sup.L.sup.u for f=1, . . . , N.sub.f and t=1, . . . ,
N.sub.t.
[0296] White noise: for each time and frequency bin white noise is
modeled as a vector of iid Gaussian random variables with mean zero
and variance N.sub.0. This document denotes the noise by
w(f,t).di-elect cons..sup.L.sup.u for f=1, . . . , N.sub.f and t=1,
. . . , N.sub.t.
[0297] Channel matrix: for each time and frequency bin the wireless
channel is represented as a matrix and is denoted by
H(f,t).di-elect cons..sup.L.sup.u.sup..times.L.sup.h for f=1, . . .
, N.sub.f and t=1, . . . , N.sub.t.
[0298] The wireless channel can be represented as a matrix which
relates the transmit and receive signals through a simple linear
equation:
y(f,t)=H(f,t).phi.(f,t)+w(f,t) (1)
[0299] for f=1, . . . ,N.sub.f and t=1, . . . , N.sub.t. FIG. 22
shows an example spectrogram of a wireless channel between a single
hub antenna and a single UE antenna. The graph is plotted with time
as the horizontal axis and frequency along the vertical axis. The
regions are shaded to indicate where the channel is strong or weak,
as denoted by the dB magnitude scale shown in FIG. 22.
[0300] Two common ways are typically used to acquire knowledge of
the channel at the hub: explicit feedback and implicit
feedback.
[0301] Explicit Feedback
[0302] In explicit feedback, the UEs measure the channel and then
transmit the measured channel back to the hub in a packet of data.
The explicit feedback may be done in three steps.
[0303] Pilot transmission: for each time and frequency bin the hub
transmits a pilot signal denoted by p(f,t).di-elect
cons..sup.L.sup.h for f=1, . . . , N.sub.f and t=1, . . . ,
N.sub.t. Unlike data, the pilot signal is known at both the hub and
the UEs.
[0304] Channel acquisition: for each time and frequency bin the UEs
receive the pilot signal distorted by the channel and white
noise:
H(f,t)p(f,t)+w(f,t), (2)
[0305] for f=1, . . . , N.sub.f and t=1, . . . , N.sub.t. Because
the pilot signal is known by the UEs, they can use signal
processing to compute an estimate of the channel, denoted by
H(f,t).
[0306] Feedback: the UEs quantize the channel estimates H(f,t) into
a packet of data. The packet is then transmitted to the hub.
[0307] The advantage of explicit feedback is that it is relatively
easy to implement. The disadvantage is the large overhead of
transmitting the channel estimates from the UEs to the hub.
[0308] Implicit Feedback
[0309] Implicit feedback is based on the principle of reciprocity
which relates the uplink channel (UEs transmitting to the hub) to
the downlink channel (hub transmitting to the UEs). FIG. 23 shows
an example configuration of uplink and downlink channels between a
hub and multiple UEs.
[0310] Specifically, denote the uplink and downlink channels by
H.sub.up and H respectively, then:
H(f,t)=A H.sub.up.sup.T(f,t)B, (3)
[0311] for f=1, . . . , N.sub.f and t=1, . . . , N.sub.t. Where
H.sub.up.sup.T(f,t) denotes the matrix transpose of the uplink
channel. The matrices A.di-elect
cons..sup.L.sup.u.sup..times.L.sup.u and B.di-elect
cons..sup.L.sup.h.sup..times.L.sup.h represent hardware
non-idealities. By performing a procedure called reciprocity
calibration, the effect of the hardware non-idealities can be
removed, thus giving a simple relationship between the uplink and
downlink channels:
H(f,t)=H.sub.up.sup.T(f,t) (4)
[0312] The principle of reciprocity can be used to acquire channel
knowledge at the hub. The procedure is called implicit feedback and
consists of three steps.
[0313] Reciprocity calibration: the hub and UEs calibrate their
hardware so that equation (4) holds.
[0314] Pilot transmission: for each time and frequency bin the UEs
transmits a pilot signal denoted by p(f,t).di-elect
cons..sup.L.sup.u for f=1, . . . , N.sub.f and t=1, . . . ,
N.sub.t. Unlike data, the pilot signal is known at both the hub and
the UEs.
[0315] Channel acquisition: for each time and frequency bin the hub
receives the pilot signal distorted by the uplink channel and white
noise:
H.sub.up(f,t)p(f,t)+w(f,t) (5)
[0316] for f=1, . . . , N.sub.f and t=1, . . . , N.sub.t. Because
the pilot signal is known by the hub, it can use signal processing
to compute an estimate of the uplink channel, denoted by (f,t).
Because reciprocity calibration has been performed the hub can take
the transpose to get an estimate of the downlink channel, denoted
by H(f,t).
[0317] The advantage of implicit feedback is that it allows the hub
to acquire channel knowledge with very little overhead; the
disadvantage is that reciprocity calibration is difficult to
implement.
[0318] Channel Prediction
[0319] Using either explicit or implicit feedback, the hub acquires
estimates of the downlink wireless channel at certain times denoted
by s.sub.1, s.sub.2, . . . , s.sub.n using these estimates it must
then predict what the channel will be at future times when the
precoding will be performed, denoted by t.sub.1, t.sub.2, . . . ,
t.sub.m. FIG. 24 shows this setup in which "snapshots" of channel
are estimated, and based on the estimated snapshots, a prediction
is made regarding the channel at a time in the future. As depicted
in FIG. 24, channel estimates may be available across the frequency
band at a fixed time slots, and based on these estimates, a
predicated channel is calculated.
[0320] There are tradeoffs when choosing the feedback times
s.sub.1, s.sub.2, . . . , s.sub.n.
[0321] Latency of extrapolation: Refers to the temporal distance
between the last feedback time, s.sub.n, and the first prediction
time, t.sub.1, determines how far into the future the hub needs to
predict the channel. If the latency of extrapolation is large, then
the hub has a good lead time to compute the pre-coding filters
before it needs to apply them. On the other hand, larger latencies
give a more difficult prediction problem.
[0322] Density: how frequent the hub receives channel measurements
via feedback determines the feedback density. Greater density leads
to more accurate prediction at the cost of greater overhead.
[0323] There are many channel prediction algorithms in the
literature. They differ by what assumptions they make on the
mathematical structure of the channel. The stronger the assumption,
the greater the ability to extrapolate into the future if the
assumption is true. However, if the assumption is false then the
extrapolation will fail. For example:
[0324] Polynomial extrapolation: assumes the channel is smooth
function. If true, can extrapolate the channel a very short time
into the future.apprxeq.0.5 ms.
[0325] Bandlimited extrapolation: assumes the channel is a
bandlimited function. If true, can extrapolated a short time into
the future.apprxeq.1 ms.
[0326] MUSIC extrapolation: assumes the channel is a finite sum of
waves. If true, can extrapolate a long time into the
future.apprxeq.10 ms.
[0327] Precoding Filter Computation and Application
[0328] Using extrapolation, the hub computes an estimate of the
downlink channel matrix for the times the pre-coded data will be
transmitted. The estimates are then used to construct precoding
filters. Precoding is performed by applying the filters on the data
the hub wants the UEs to receive. Before going over details we
introduce notation.
[0329] Channel estimate: for each time and frequency bin the hub
has an estimate of the downlink channel which we denote by
H(f,t).di-elect cons..sup.L.sup.u.sup..times.L.sup.h for f=1, . . .
, N.sub.f and t=1, . . . , N.sub.t.
[0330] Precoding filter: for each time and frequency bin the hub
uses the channel estimate to construct a precoding filter which we
denote by W(f,t).di-elect cons..sup.L.sup.h.sup..times.L.sup.u for
f=1, . . . , N.sub.f and t=1, . . . , N.sub.t.
[0331] Data: for each time and frequency bin the UE wants to
transmit a vector of data to the UEs which we denote by
x(f,t).di-elect cons..sup.L.sup.u for f=1, . . . , N.sub.f and t=1,
. . . , N.sub.t.
[0332] Hub Energy Constraint
[0333] When the precoder filter is applied to data, the hub power
constraint is an important consideration. We assume that the total
hub transmit energy cannot exceed N.sub.fN.sub.tL.sub.h. Consider
the pre-coded data:
W(f,t).times.(f,t), (6)
[0334] for f=1, . . . , N.sub.f and t=1, . . . , N.sub.t. To ensure
that the pre-coded data meets the hub energy constraints the hub
applies normalization, transmitting:
.lamda.W(f,t).times.(f,t), (7)
[0335] for f=1, . . . , N.sub.f and t=1, . . . , N.sub.t. Where the
normalization constant .lamda. is given by:
.lamda. = N f N t L h .SIGMA. f , t W ( f , t ) .times. ( f , t ) 2
( 8 ) ##EQU00005##
[0336] Receiver SNR
[0337] The pre-coded data then passes through the downlink channel,
the UEs receive the following signal:
.lamda.H(f,t)W(f,t).times.(f,t)+w(f,t), (9)
[0338] for f=1, . . . , N.sub.f and t=1, . . . , N.sub.t. The UE
then removes the normalization constant, giving a soft estimate of
the data:
x soft ( f , t ) = H ( f , t ) W ( f , t ) x ( f , t ) + 1 .lamda.
w ( f , t ) , ( 10 ) ##EQU00006##
[0339] for f=1, . . . , N.sub.f and t=1, . . . , N.sub.t. The error
of the estimate is given by:
x soft ( f , t ) - x ( f , t ) = H ( f , t ) W ( f , t ) x ( f , t
) - x ( f , t ) + 1 .lamda. w ( f , t ) , ( 11 ) ##EQU00007##
[0340] The error of the estimate can be split into two terms. The
term H(f,t)W(f,t)-x(f,t) is the interference experienced by the UEs
while the term
1 .lamda. w ( f , t ) ##EQU00008##
gives the noise experienced by the UEs.
[0341] When choosing a pre-coding filter there is a tradeoff
between interference and noise. We now review the two most popular
pre-coder filters: zero-forcing and regularized zero-forcing.
[0342] Zero Forcing Precoder
[0343] The hub constructs the zero forcing pre-coder (ZFP) by
inverting its channel estimate:
W.sub.ZF(f,t)=(H*(f,t)H(f,t)).sup.-1H*(f,t), (12)
[0344] for f=1, . . . , N.sub.f and t=1, . . . , N.sub.t. The
advantage of ZPP is that the UEs experience little interference (if
the channel estimate is perfect then the UEs experience no
interference). The disadvantage of ZFP is that the UEs can
experience a large amount of noise. This is because at time and
frequency bins where the channel estimate H(f,t) is very small the
filter W.sub.ZF (f,t) will be very large, thus causing the
normalization constant .lamda. to be very small giving large noise
energy. FIG. 25 demonstrates this phenomenon for a SISO
channel.
[0345] Regularized Zero-Forcing Pre-Coder (rZFP)
[0346] To mitigates the effect of channel nulls (locations where
the channel has very small energy) the regularized zero forcing
precoder (rZFP) is constructed be taking a regularized inverse of
its channel estimate:
W.sub.rZF(f,t)=(H*(f,t)H(f,t)+.alpha.I).sup.-1H*(f,t), (13)
[0347] for f=1, . . . , N.sub.f and t=1, . . . , N.sub.t. Where
.alpha.>0 is the normalization constant. The advantage of rZFP
is that the noise energy is smaller compared to ZPF. This is
because rZFP deploys less energy in channel nulls, thus the
normalization constant .lamda. is larger giving smaller noise
energy. The disadvantage of rZFP is larger interference compared to
ZFP. This is because the channel is not perfectly inverted (due to
the normalization constant), so the UEs will experience residual
interference. FIG. 26 demonstrates this phenomenon for a SISO
channel.
[0348] As described above, there are three components to a
precoding system: a channel feedback component, a channel
prediction component, and a pre-coding filter component. The
relationship between the three components is displayed in FIG.
27.
[0349] OTFS Precoding System
[0350] Various techniques for implementing OTFS precoding system
are discussed. Some disclosed techniques can be used to provide
unique ability to shape the energy distribution of the transmission
signal. For example, energy distribution may be such that the
energy of the signal will be high in regions of time frequency and
space where the channel information and the channel strength are
strong. Conversely, the energy of the signal will be low in regions
of time frequency and space where the channel information or the
channel strength are weak.
[0351] Some embodiments may be described with reference to three
main blocks, as depicted in FIG. 28.
[0352] Channel prediction: During channel prediction, second order
statistics are used to build a prediction filter along with the
covariance of the prediction error.
[0353] Optimal precoding filter: using knowledge of the predicted
channel and the covariance of the prediction error: the hub
computes the optimal precoding filter. The filter shapes the
spatial energy distribution of the transmission signal.
[0354] Vector perturbation: using knowledge of the predicted
channel, precoding filter, and prediction error, the hub perturbs
the transmission signal. By doing this the hub shapes the time,
frequency, and spatial energy distribution of the transmission
signal.
[0355] Review of OTFS Modulation
[0356] A modulation is a method to transmit a collection of finite
symbols (which encode data) over a fixed allocation of time and
frequency. A popular method used today is Orthogonal Frequency
Division Multiplexing (OFDM) which transmits each finite symbol
over a narrow region of time and frequency (e.g., using subcarriers
and timeslots). In contrast, Orthogonal Time Frequency Space (OTFS)
transmits each finite symbol over the entire allocation of time and
frequency. Before going into details, we introduce terminology and
notation.
[0357] We call the allocation of time and frequency a frame. We
denote the number of subcarriers in the frame by N.sub.f. We denote
the subcarrier spacing by df. We denote the number of OFDM symbols
in the frame by N.sub.t. We denote the OFDM symbol duration by dt.
We call a collection of possible finite symbols an alphabet,
denoted by A.
[0358] A signal transmitted over the frame, denoted by .phi., can
be specified by the values it takes for each time and frequency
bin:
.phi.(f,t).di-elect cons., (14)
[0359] for f=1, . . . , N.sub.f and t=1, . . . , N.sub.t.
[0360] FIG. 29 shows an example of a frame along time (horizontal)
axis and frequency (vertical) axis. FIG. 30 shows an example of the
most commonly used alphabet: Quadrature Amplitude Modulation
(QAM).
[0361] OTFS Modulation
[0362] Suppose a transmitter has a collection of N.sub.fN.sub.t QAM
symbols that the transmitter wants to transmit over a frame,
denoted by:
x(f,t).di-elect cons.A, (15)
[0363] for f=1, . . . , N.sub.f and t=1, . . . , N.sub.t. OFDM
works by transmitting each QAM symbol over a single time frequency
bin:
.phi.(f,t)=x(f,t), (16A)
[0364] for f=1, . . . , N.sub.f and t=1, . . . , N.sub.t. The
advantage of OFDM is its inherent parallelism, this makes many
computational aspects of communication very easy to implement. The
disadvantage of OFDM is fading, that is, the wireless channel can
be very poor for certain time frequency bins. Performing pre-coding
for these bins is very difficult.
[0365] The OTFS modulation is defined using the delay Doppler
domain, which is relating to the standard time frequency domain by
the two-dimensional Fourier transform.
[0366] The delay dimension is dual to the frequency dimension.
There are N.sub..tau. delay bins with N.sub..tau.=N.sub.f. The
Doppler dimension is dual to the time dimension. There are
N.sub..nu. Doppler bins with N.sub..nu.=N.sub.t.
[0367] A signal in the delay Doppler domain, denoted by .PHI., is
defined by the values it takes for each delay and Doppler bin:
.PHI.(.tau.,.nu.).di-elect cons., (16B)
[0368] for .tau.=1, . . . , N.sub..tau. and .nu.=1, . . . ,
N.sub..nu..
[0369] Given a signal .PHI. in the delay Doppler domain, some
transmitter embodiments may apply the two-dimensional Fourier
transform to define a signal .phi. in the time frequency
domain:
.phi.(f,t)=(F.PHI.)(f,t), (17)
[0370] for f=1, . . . , N.sub.f and t=1, . . . , N.sub.t. Where F
denotes the two-dimensional Fourier transform.
[0371] Conversely, given a signal .phi. in the time frequency
domain, transmitter embodiments could apply the inverse
two-dimensional Fourier transform to define a signal .PHI. in the
delay Doppler domain:
.PHI.(.tau.,.nu.)=(F.sup.-1.phi.)(.tau.,.nu.), (18)
[0372] for .tau.=1, . . . , N.sub..tau. and .nu.=1, . . . ,
N.sub..nu..
[0373] FIG. 31 depicts an example of the relationship between the
delay Doppler and time frequency domains.
[0374] The advantage of OTFS is that each QAM symbol is spread
evenly over the entire time frequency domain (by the
two-two-dimensional Fourier transform), therefore each QAM symbol
experience all the good and bad regions of the channel thus
eliminating fading. The disadvantage of OTFS is that the QAM
spreading adds computational complexity.
[0375] MMSE Channel Prediction
[0376] Channel prediction is performed at the hub by applying an
optimization criterion, e.g., the Minimal Mean Square Error (MMSE)
prediction filter to the hub's channel estimates (acquired by
either implicit or explicit feedback). The MMSE filter is computed
in two steps. First, the hub computes empirical estimates of the
channel's second order statistics. Second, using standard
estimation theory, the hub uses the second order statistics to
compute the MMSE prediction filter. Before going into details, we
introduce notation:
[0377] We denote the number of antennas at the hub by L.sub.h. We
denote the number of UE antennas by L.sub.u. We index the UE
antennas by u=1, . . . , L.sub.u. We denote the number frequency
bins by N.sub.f. We denote the number of feedback times by
n.sub.past. We denote the number of prediction times by
n.sub.future FIG. 32 shows an example of an extrapolation process
setup.
[0378] For each UE antenna, the channel estimates for all the
frequencies, hub antennas, and feedback times can be combined to
form a single N.sub.fL.sub.hn.sub.past dimensional vector. We
denote this by:
H.sub.past(u).di-elect
cons..sup.N.sup.f.sup.L.sup.h.sup.n.sup.past, (19)
[0379] Likewise, the channel values for all the frequencies, hub
antennas, and prediction times can be combined to form a single
N.sub.fL.sub.hn.sub.future dimensional vector. We denote this
by:
H.sub.future(u).di-elect
cons..sup.N.sup.f.sup.L.sup.h.sup.n.sup.future (20)
[0380] In typical implementations, these are extremely high
dimensional vectors and that in practice some form of compression
should be used. For example, principal component compression may be
one compression technique used.
[0381] Empirical Second Order Statistics
[0382] Empirical second order statistics are computed separately
for each UE antenna in the following way:
[0383] At fixed times, the hub receives through feedback N samples
of H.sub.past(u) and estimates of H.sub.future(u) We denote them
by: H.sub.past(u).sub.i and H.sub.future(u).sub.i for i=1, . . . ,
N.
[0384] The hub computes an estimate of the covariance of
H.sub.past(u), which we denote by {circumflex over
(R)}.sub.past(u):
R ^ past ( u ) = 1 N i = 1 N H ^ past ( u ) i H ^ past ( u ) i * (
21 ) ##EQU00009##
[0385] The hub computes an estimate of the covariance of
H.sub.future (u), which we denote by {circumflex over
(R)}.sub.future(u):
R ^ future ( u ) = 1 N i = 1 N H ^ future ( u ) i H ^ future ( u )
i * ( 22 ) ##EQU00010##
[0386] The hub computes an estimate of the correlation between
H.sub.future (u) and H.sub.past(u), which we denote by {circumflex
over (R)}.sub.past,future(u):
R ^ future , past ( u ) = 1 N i = 1 N H ^ future ( u ) i H ^ past (
u ) i * ( 23 ) ##EQU00011##
[0387] In typical wireless scenarios (pedestrian to highway speeds)
the second order statistics of the channel change slowly (on the
order of 1-10 seconds). Therefore, they should be recomputed
relatively infrequently. Also, in some instances it may be more
efficient for the UEs to compute estimates of the second order
statistics and feed these back to the hub.
[0388] MMSE Prediction Filter
[0389] Using standard estimation theory, the second order
statistics can be used to compute the MMSE prediction filter for
each UE antenna:
C(u)={circumflex over (R)}.sub.future,past(u){circumflex over
(R)}.sub.past.sup.-1(u), (24)
[0390] Where C(u) denotes the MMSE prediction filter. The hub can
now predict the channel by applying feedback channel estimates into
the MMSE filter:
H.sub.future(u)=C(u)H.sub.past(u). (25)
[0391] Prediction Error Variance
[0392] We denote the MMSE prediction error by
.DELTA.H.sub.future(u), then:
H.sub.future(u)=H.sub.future(u)+.DELTA.H.sub.future(u). (26)
[0393] We denote the covariance of the MMSE prediction error by
R.sub.error(u), with:
R.sub.error(u)=[.DELTA.H.sub.future(u).DELTA.H.sub.future(u)*].
(27)
[0394] Using standard estimation theory, the empirical second order
statistics can be used to compute an estimate of
R.sub.error(u):
{circumflex over (R)}.sub.error(u)=C(U){circumflex over
(R)}.sub.past(u)C(u)*-C(u){circumflex over
(R)}.sub.future,past(u)*-{circumflex over
(R)}.sub.future,past(u)C(u)*+{circumflex over (R)}.sub.future(u)
(28)
[0395] Simulation Results
[0396] We now present simulation results illustrating the use of
the MMSE filter for channel prediction. Table 3 gives the
simulation parameters and FIG. 33 shows the extrapolation setup for
this example.
TABLE-US-00003 TABLE 3 Subcarrier spacing 15 kHz Number of
subcarriers 512 Delay spread 3 .mu.s Doppler spread 600 Hz Number
of channel feedback estimates 5 Spacing of channel feedback
estimates 10 ms Prediction range 0-20 ms into the future
[0397] Fifty samples of H.sub.past and H.sub.future were used to
compute empirical estimates of the second order statistics. The
second order statistics were used to compute the MMSE prediction
filter. FIG. 34 shows the results of applying the filter. The
results have shown that the prediction is excellent at predicting
the channel, even 20 ms into the future.
[0398] Block Diagrams
[0399] In some embodiments, the prediction is performed
independently for each UE antenna. The prediction can be separated
into two steps:
[0400] 1) Computation of the MMSE prediction filter and prediction
error covariance: the computation can be performed infrequently (on
the order of seconds). The computation is summarized in FIG. 35.
Starting from left in FIG. 35, first, feedback channel estimates
are collected. Next, the past, future and future/past correlation
matrices are computed. Next the filter estimate C(u) and the error
estimate are computed.
[0401] 2) Channel prediction: is performed every time pre-coding is
performed. The procedure is summarized in FIG. 36.
[0402] Optimal Precoding Filter
[0403] Using MMSE prediction, the hub computes an estimate of the
downlink channel matrix for the allocation of time and frequency
the pre-coded data will be transmitted. The estimates are then used
to construct precoding filters. Precoding is performed by applying
the filters on the data the hub wants the UEs to receive.
Embodiments may derive the "optimal" precoding filters as follows.
Before going over details we introduce notation.
[0404] Frame (as defined previously): precoding is performed on a
fixed allocation of time and frequency, with N.sub.f frequency bins
and N.sub.t time bins. We index the frequency bins by: f=1, . . . ,
N.sub.f. We index the time bins by t=1, . . . , N.sub.t.
[0405] Channel estimate: for each time and frequency bin the hub
has an estimate of the downlink channel which we denote by
H(f,t).di-elect cons..sup.L.sup.u.sup..times.L.sup.h.
[0406] Error correlation: we denote the error of the channel
estimates by .DELTA.H(f,t), then:
H(f,t)=H(f,t)+.DELTA.H(f,t), (29)
[0407] We denote the expected matrix correlation of the estimation
error by R.sub..DELTA.H(f,t).di-elect
cons..sup.L.sup.h.sup..times.L.sup.h, with:
R.sub..DELTA.H(f,t)=[.DELTA.H(f,t)*.DELTA.H(f,t)]. (30)
[0408] The hub can be easily compute these using the prediction
error covariance matrices computed previously: {circumflex over
(R)}.sub.error(U) for u=1, . . . , L.sub.u.
[0409] Signal: for each time and frequency bin the UE wants to
transmit a signal to the UEs which we denote by s(f,t).di-elect
cons..sup.L.sup.u.
[0410] Precoding filter: for each time and frequency bin the hub
uses the channel estimate to construct a precoding filter which we
denote by W(f,t).di-elect cons..sup.L.sup.h.sup..times.L.sup.h.
[0411] White noise: for each time and frequency bin the UEs
experience white noise which we denote by n(f,t).di-elect
cons..sup.L.sup.u. We assume the white noise is iid Gaussian with
mean zero and variance N.sub.0.
[0412] Hub Energy Constraint
[0413] When the precoder filter is applied to data, the hub power
constraint may be considered. We assume that the total hub transmit
energy cannot exceed N.sub.fN.sub.tL.sub.h. Consider the pre-coded
data:
W(f,t)s(f,t), (31)
[0414] To ensure that the pre-coded data meets the hub energy
constraints the hub applies normalization, transmitting:
.lamda.W(f,t)s(f,t), (32)
[0415] Where the normalization constant .lamda. is given by:
.lamda. = N f N t L h f , t W ( f , t ) s ( f , t ) 2 ( 33 )
##EQU00012##
[0416] Receiver SINR
[0417] The pre-coded data then passes through the downlink channel,
the UEs receive the following signal:
.DELTA.H(f,t)W(f,t)s(f,t)+n(f,t), (34)
[0418] The UEs then removes the normalization constant, giving a
soft estimate of the signal:
s soft ( f , t ) = H ( f , t ) W ( f , t ) s ( f , t ) + 1 .lamda.
n ( f , t ) . ( 35 ) ##EQU00013##
[0419] The error of the estimate is given by:
s soft ( f , t ) - s ( f , t ) = H ( f , t ) W ( f , t ) s ( f , t
) - s ( f , t ) + 1 .lamda. n ( f , t ) . ( 36 ) ##EQU00014##
[0420] The error can be decomposed into two independent terms:
interference and noise. Embodiments can compute the total expected
error energy:
expected error energy = f = 1 N f t = 1 N t s soft ( f , t ) - s (
f , t ) 2 = f = 1 N f t = 1 N t H ( f , t ) W ( f , t ) s ( f , t )
- s ( f , t ) 2 + 1 .lamda. 2 n ( f , t ) 2 = f = 1 N f t = 1 N t (
H ^ ( f , t ) W ( f , t ) s ( f , t ) - s ( f , t ) ) * ( H ^ ( f ,
t ) W ( f , s ) s ( f , t ) - s ( f , t ) ) + ( W ( f , t ) s ( f ,
t ) ) * ( R .DELTA. H ( f , t ) + N 0 L u L h I ) ( W ( f , t ) s (
f , t ) ) ( 37 ) ##EQU00015##
[0421] Optimal Precoding Filter
[0422] We note that the expected error energy is convex and
quadratic with respect to the coefficients of the precoding filter.
Therefore, calculus can be used to derive the optimal precoding
filter:
W o p t ( f , t ) = ( H ^ ( f , t ) * H ^ ( f , t ) + R .DELTA. H (
f , t ) + N 0 L u L h I ) - 1 H ^ ( f , t ) * ( 38 )
##EQU00016##
[0423] Accordingly, some embodiments of an OTFS precoding system
use this filter (or an estimate thereof) for precoding.
[0424] Simulation Results
[0425] We now present a simulation result illustrating the use of
the optimal precoding filter. The simulation scenario was a hub
transmitting data to a single UE. The channel was non line of
sight, with two reflector clusters: one cluster consisted of static
reflectors, the other cluster consisted of moving reflectors. FIG.
37 illustrates the channel geometry, with horizontal and vertical
axis in units of distance. It is assumed that the hub has good
Channel Side Information (CSI) regarding the static cluster and
poor CSI regarding the dynamic cluster. The optimal precoding
filter was compared to the MMSE precoding filter. FIG. 38A displays
the antenna pattern given by the MMSE precoding filter. It can be
seen that the energy is concentrated at .+-.45.degree., that is,
towards the two clusters. The UE SINR is 15.9 dB, the SINR is
relatively low due to the hub's poor CSI for the dynamic
cluster.
[0426] FIG. 38B displays the antenna pattern given by the optimal
precoding filter as described above, e.g., using equation (38). In
this example, the energy is concentrated at 45.degree., that is,
toward the static cluster. The UE SINR is 45.3 dB, the SINR is high
(compared to the MMSE case) due to the hub having good CSI for the
static reflector.
[0427] The simulation results depicted in FIGS. 38A and 38B
illustrate the advantage of the optimal pre-coding filter. The
filter it is able to avoid sending energy towards spatial regions
of poor channel CSI, e.g., moving regions.
[0428] Example Block Diagrams
[0429] Precoding is performed independently for each time frequency
bin. The precoding can be separated into three steps:
[0430] [1] Computation of error correlation: the computation be
performed infrequently (on the order of seconds). The computation
is summarized in FIG. 39.
[0431] [2] Computation of optimal precoding filter: may be
performed every time pre-coding is performed. The computation is
summarized in FIG. 40.
[0432] [3] Application of the optimal precoding filter: may be
performed every time pre-coding is performed. The procedure is
summarized in FIG. 41.
[0433] OTFS Vector Perturbation
[0434] Before introducing the concept of vector perturbation, we
outline the application of the optimal pre-coding filter to
OTFS.
[0435] OTFS Optimal Precoding
[0436] In OTFS, the data to be transmitted to the UEs are encoded
using QAMs in the delay-Doppler domain. We denote this QAM signal
by x, then:
x(.tau.,.nu.).di-elect cons.A.sup.L.sup.u, (39)
[0437] for .tau.=1, . . . , N.sub..tau. and .nu.=1, . . . ,
N.sub..nu.. A denotes the QAM constellation. Using the
two-dimensional Fourier transform the signal can be represented in
the time frequency domain. We denote this representation by X:
X(f,t)=(Fx)(f,t), (40)
[0438] for f=1, . . . , N.sub.f and t=1, . . . , N.sub.t. F denotes
the two-dimensional Fourier transform. The hub applies the optimal
pre-coding filter to X and transmit the filter output over the
air:
.lamda.W.sub.opt(f,t)X(f,t), (41)
[0439] for f=1, . . . , N.sub.f and t=1, . . . , N.sub.t. .lamda.
denotes the normalization constant. The UEs remove the
normalization constant giving a soft estimate of X:
X soft ( f , t ) = H ( f , t ) W opt ( f , t ) X ( f , t ) + 1
.lamda. w ( f , t ) , ( 42 ) ##EQU00017##
[0440] for f=1, . . . , N.sub.f and t=1, . . . , N.sub.t. The term
w(f,t) denotes white noise. We denote the error of the soft
estimate by E:
E(f,t)=X.sub.soft(f,t)-X(f,t), (43)
[0441] for f=1, . . . , N.sub.f and t=1, . . . , N.sub.t. The
expected error energy was derived earlier in this document:
expected error energy = f = 1 N f t = 1 N t X soft ( f , t ) - X (
f , t ) 2 = f = 1 N f t = 1 N t X ( f , t ) * M error ( f , t ) X (
f , t ) ( 44 ) ##EQU00018##
[0442] Where:
M error ( f , t ) = ( H ^ ( f , t ) W o p t ( f , t ) - 1 ) * ( H ^
( f , t ) W opt ( f , t ) - 1 ) + W opt ( f , t ) * ( R .DELTA. H (
f , t ) + N 0 L u L h ) W opt ( f , t ) ( 45 ) ##EQU00019##
[0443] We call the positive definite matrix M.sub.error(f,t) the
error metric.
[0444] Vector Perturbation
[0445] In vector perturbation, the hub transmits a perturbed
version of the QAM signal:
x(.tau.,.nu.)+p(.tau.,.nu.), (46)
[0446] for .tau.=1, . . . , N.sub..tau. and .nu.=1, . . . ,
N.sub..nu.. Here, p(.tau.,.nu.) denotes the perturbation signal.
The perturbed QAMs can be represented in the time frequency
domain:
X(f,t)+P(f,t)=(Fx)(f,t)+(Fp)(f,t), (47)
[0447] for f=1, . . . , N.sub.f and t=1, . . . , N.sub.t. The hub
applies the optimal pre-coding filter to the perturbed signal and
transmits the result over the air. The UEs remove the normalization
constant giving a soft estimate of the perturbed signal:
X(f,t)+P(f,t)+E(f,t), (48)
[0448] for f=1, . . . , N.sub.f and t=1, . . . , N.sub.t. Where E
denotes the error of the soft estimate. The expected energy of the
error is given by:
expected error
energy=.SIGMA..sub.f=1.sup.N.sup.f.SIGMA..sub.t=1.sup.N.sup.t(X(f,t)+P(f,-
t))*M.sub.error(f,t)(X(f,t)+P(f,t)) (49)
[0449] The UEs then apply an inverse two dimensional Fourier
transform to convert the soft estimate to the delay Doppler
domain:
x(.tau.,.nu.)+p(.tau.,.nu.)+e(.tau.,.nu.), (50)
[0450] for .tau.=1, . . . , N.sub..tau. and .nu.=1, . . . ,
N.sub..nu.. The UEs then remove the perturbation p(.tau.,.nu.) for
each delay Doppler bin to recover the QAM signal x.
[0451] Collection of Vector Perturbation Signals
[0452] One question is: what collection of perturbation signals
should be allowed? When making this decision, there are two
conflicting criteria:
[0453] 1) The collection of perturbation signals should be large so
that the expected error energy can be greatly reduced.
[0454] 2) The collection of perturbation signals should be small so
the UE can easily remove them (reduced computational
complexity):
x(.tau.,.nu.)+p(.tau.,.nu.).fwdarw.x(.tau.,.nu.) (51)
[0455] Coarse Lattice Perturbation
[0456] An effective family of perturbation signals in the
delay-Doppler domain, which take values in a coarse lattice:
p(.tau.,.nu.).di-elect cons.B.sup.L.sup.u, (52)
[0457] for T=1, . . . , N.sub..tau. and .nu.=1, . . . , N.sub..nu..
Here, B denotes the coarse lattice. Specifically, if the QAM
symbols lie in the box: [-r,r].times.j[-r, r] we take as our
perturbation lattice B=2r+2rj. We now illustrate coarse lattice
perturbation with an example.
Examples
[0458] Consider QPSK (or 4-QAM) symbols in the box
[-2,2].times.j[-2,2]. The perturbation lattice is then B=4+4. FIG.
42 illustrates the symbols and the lattice. Suppose the hub wants
to transmit the QPSK symbol 1+1j to a UE. Then there is an infinite
number of coarse perturbations of 1+1j that the hub can transmit.
FIG. 43 illustrates an example. The hub selects one of the possible
perturbations and transmits it over the air. FIG. 44 illustrates
the chosen perturbed symbol, depicted with a single solid
circle.
[0459] The UE receives the perturbed QPSK symbol. The UE then
removes the perturbation to recover the QPSK symbol. To do this,
the UE first searches for the coarse lattice point closest to the
received signal. FIG. 45 illustrates this.
[0460] The UE subtracts the closest lattice point from the received
signal, thus recovering the QPSK symbol 1+1j. FIG. 46 illustrates
this process.
[0461] Finding Optimal Coarse Lattice Perturbation Signal
[0462] The optimal coarse lattice perturbation signal, p.sub.opt,
is the one which minimizes the expected error energy:
P.sub.opt=argmin.sub.p.SIGMA..sub.f=1.sup.N.sup.f.SIGMA..sub.t=1.sup.N.s-
up.t(X(f,t)+P(f,t))*M.sub.error(f,t)(X(f,t)+P(f,t)) (53)
[0463] The optimal coarse lattice perturbation signal can be
computed using different methods. A computationally efficient
method is a form of Thomlinson-Harashima precoding which involves
applying a DFE filter at the hub.
[0464] Coarse Lattice Perturbation Example
[0465] We now present a simulation result illustrating the use of
coarse lattice perturbation. The simulation scenerio was a hub
antenna transmitting to a single UE antenna. Table 4 displays the
modulation paramaters. Table 5 display the channel paramaters for
this example.
TABLE-US-00004 TABLE 4 Subcarrier spacing 30 kHz Number of
subcarriers 256 OFDM symbols per frame 32 QAM order Infinity
(uniform in the unit box)
TABLE-US-00005 TABLE 5 Number of reflectors 20 Delay spread 2 .mu.s
Doppler spread 1 KHz Noise variance -35 dB
[0466] FIG. 47 displays the channel energy in the time (horizontal
axis) and frequency (vertical axis) domain.
[0467] Because this is a SISO (single input single output) channel,
the error metric M.sub.error(f,t) is a positive scaler for each
time frequency bin. The expected error energy is given by
integrating the product of the error metric with the perturbed
signal energy:
expected error
energy=.SIGMA..sub.t=1.sup.N.sup.f.SIGMA..sub.t=1.sup.N.sup.tM.sub.error(-
f,t)|X(f,t)+P(f,t)|.sup.2 (54)
[0468] FIG. 48 displays an example of the error metric. One hundred
thousand random QAM signals were generated. For each QAM signal,
the corresponding optimal perturbation signal was computed using
Thomlinson-Harashima precoding. FIG. 49 compares the average energy
of the QAM signals with the average energy of the perturbed QAM
signals. The energy of QAM signals is white (evenly distributed)
while the energy of the perturbed QAM signals is colored (strong in
some time frequency regions and weak in others). The average error
energy of the unperturbed QAM signal was -24.8 dB. The average
error energy of the perturbed QAM signal was -30.3 dB. The
improvement in error energy can be explained by comparing the
energy distribution of the perturbed QAM signal with the error
metric.
[0469] FIG. 50 shows a comparison of an example error metric with
an average perturbed QAM energy. The perturbed QAM signal has high
energy where the error metric is low, conversely it has low energy
where the error metric is high.
[0470] The simulation illustrates the gain from using vector
perturbation: shaping the energy of the signal to avoid time
frequency regions where the error metric is high.
[0471] Block Diagrams
[0472] Vector perturbations may be performed in three steps. First,
the hub perturbs the QAM signal. Next, the perturbed signal is
transmitted over the air using the pre-coding filters. Finally, the
UEs remove the perturbation to recover the data.
[0473] Computation of error metric: the computation can be
performed independently for each time frequency bin. The
computation is summarized in FIG. 51. See also Eq. (45). As shown,
the error metric is calculated using channel prediction estimate,
the optimal coding filter and error correlation estimate.
[0474] Computation of perturbation: the perturbation is performed
on the entire delay Doppler signal. The computation is summarized
in FIG. 52. As shown, the QAM signal and the error metric are used
to compute the perturbation signal. The calculated perturbation
signal is additively applied to the QAM input signal.
[0475] Application of the optimal precoding filter: the computation
can be performed independently for each time frequency bin. The
computation is summarized in FIG. 53. The perturbed QAM signal is
processed through a two dimensional Fourier transform to generate a
2D transformed perturbed signal. The optimal precoding filter is
applied to the 2D transformed perturbed signal.
[0476] UEs removes perturbation: the computation can be FIG. 54. At
UE, the input signal received is transformed through an inverse 2D
Fourier transform. The closest lattice point for the resulting
transformed signal is determined and then removed from the 2D
transformed perturbed signal.
[0477] Spatial Tomlinson Harashima Precoding
[0478] This section provides additional details of achieving
spatial precoding and the beneficial aspects of using Tomlinson
Harashima precoding algorithm in implementing spatial precoding in
the delay Doppler domain. The embodiments consider a flat channel
(with no frequency or time selectivity).
[0479] Review of Linear Precoding
In precoding, the hub wants to transmit a vector of QAMs to the
UEs. We denote this vector by x.di-elect cons..sup.L.sup.u. The hub
has access to the following information: [0480] An estimate of the
downlink channel, denoted by: H.di-elect
cons..sup.L.sup.u.sup..times.L.sup.h. [0481] The matrix covariance
of the channel estimation error, denoted by:
R.sub..DELTA.H.di-elect cons..sup.L.sup.h.sup..times.L.sup.h. From
this information, the hub computes the "optimal" precoding filter,
which minimizes the expected error energy experienced by the
UEs:
[0481] W opt = ( H ^ * H ^ + R .DELTA. H + N 0 L u L h I ) - 1 H ^
* ##EQU00020##
By applying the precoding filter to the QAM vector the hub
constructs a signal to transmit over the air: .lamda.W.sub.optx
.di-elect cons..sup.L.sup.h, where .lamda. is a constant used to
enforce the transmit energy constraints. The signal passes through
the downlink channel and is received by the UEs:
.lamda.HW.sub.optx+W,
Where w.di-elect cons..sup.L.sup.u denotes AWGN noise. The UEs
remove the normalization constant giving a soft estimate of the QAM
signal:
x+e,
where e.di-elect cons..sup.L.sup.u denotes the estimate error. The
expected error energy can be computed using the error metric:
expected error energy=x*M.sub.errorx
where M.sub.error is a positive definite matrix computed by:
M error = ( H ^ W opt - I ) * ( H ^ W opt - I ) + W opt * ( R
.DELTA. H + N 0 L u L h ) W opt ##EQU00021##
[0482] Review of Vector Perturbation
The expected error energy can be greatly reduced by perturbing the
QAM signal by a vector v.di-elect cons..sup.L.sup.u. The hub now
transmits .lamda.W.sub.opt(x+v).di-elect cons..sup.L.sup.h. After
removing the normalization constant, the UEs have a soft estimate
of the perturbed QAM signal:
x+v+e
Again, the expected error energy can be computed using the error
metric:
expected error energy=(x+V)*M.sub.error(x+v)
The optimal perturbation vector minimizes the expected error
energy:
v.sub.opt=argmin.sub.v(x+V)*M.sub.error(x+v).
Computing the optimal perturbation vector is in general NP-hard,
therefore, in practice an approximation of the optimal perturbation
is computed instead. For the remainder of the document we assume
the following signal and perturbation structure:
[0483] The QAMs lie in the box [-1,1].times.j[-1, 1].
[0484] The perturbation vectors lie on the coarse lattice:
(2+2j).sup.L.sup.u.
[0485] Spatial Tomlinson Harashima Precoding
In spatial THP a filter is used to compute a "good" perturbation
vector. To this end, we make use of the Cholesky decomposition of
the positive definite matrix M.sub.error:
M.sub.error=U*DU,
where D is a diagonal matrix with positive entries and U is unit
upper triangular. Using this decomposition, the expected error
energy can be expressed as:
expected error
energy=(U(x+v))*D(U(x+v))=z*Dz=.SIGMA..sub.n=1.sup.L.sup.uD(n,n)|z(n)|.su-
p.2,
where z=U(x+v). We note that minimizing the expected error energy
is equivalent to minimizing the energy of the z entries, where:
z ( L u ) = x ( L u ) + v ( L u ) , z ( n ) = x ( n ) + v ( n ) + m
= n + 1 L u U ( n , m ) ( x ( m ) + v ( m ) ) , ##EQU00022##
for n=1, 2, . . . , L.sub.u-1. Spatial THP iteratively choses a
perturbation vector in the following way.
v ( L u ) = 0 ##EQU00023## Suppose v ( n + 1 ) , v ( n + 2 ) , , v
( L u ) have been chosen , then : ##EQU00023.2## v ( n ) = - ( 2 +
2 j ) ( x ( n ) + m = n + 1 L u U ( n , m ) ( x ( m ) + v ( m ) ) )
##EQU00023.3##
[0486] where denotes projection onto the coarse lattice. We note
that by construction the coarse perturbation vector bounds the
energy of the entries of z by two. FIG. 55 displays a block diagram
of spatial THP.
[0487] Simulation Results
[0488] We now present the results of a simple simulation to
illustrate the use of spatial THP. Table 6 summarizes the
simulation setup.
TABLE-US-00006 TABLE 6 Simulation setup Number of hub antennas 2
Number of UEs 2 (one antenna each) Channel condition number 10 dB
Modulation PAM infinity (data uniformly disturbed on the interval
[-1, 1]) Data noise variance -35 dB Channel noise variance -35
dB
FIG. 56 displays the expected error energy for different PAM
vectors. We note two aspects of the figure. [0489] The error energy
is low when the signal transmitted to UE1 and UE2 are similar.
Conversely, the error energy is high when the signals transmitted
to the UEs are dissimilar. We can expect this pattern to appear
when two UEs are spatially close together; in these situations, it
is advantageous to transmit the same message to both UEs. [0490]
The error energy has the shape of an ellipses. The axes of the
ellipse are defined by the eigenvectors of M.sub.error.
[0491] A large number data of PAM vectors was generated and spatial
THP was applied. FIG. 57 shows the result. Note that the perturbed
PAM vectors are clustered along the axis with low expected error
energy.
[0492] THP Enhancements
[0493] The problem of finding the optimal perturbation vector at
the transmitter is analogous to the MIMO QAM detection problem at
the receiver. Furthermore, transmitter THP is analogous to receiver
successive interference cancellation (SIC). The same improvements
used for SIC can be used for THP, for example: [0494] V-Blast, can
be used to first choose a better ordering of streams before
applying THP. [0495] K-best and sphere detection can be used to
search more perturbation vectors. [0496] Lattice reduction can be
used as a pre-processing step to THP, improving the condition
number of the Cholesky factors.
[0497] All these techniques are well known to wireless engineers.
We will only go into more depth with lattice reduction as it gives
the best performance for polynomial complexity.
[0498] Lattice Reduction Enhancement
The performance of THP depends strongly on the size of the diagonal
Cholesky factor of M.sub.error:
expected error energy = n = 1 L u D ( n , n ) z ( n ) 2 .ltoreq. 2
n = 1 L u D ( n , n ) ##EQU00024##
Lattice reduction is a pre-pocessing step to THP which improves
performance by relating the old Cholesky factorization U*DU to a
new Cholesky factorization U.sub.LR*D.sub.LRU.sub.LR, with:
n = 1 L u D L R ( n , n ) .ltoreq. n = 1 L u D ( n , n )
##EQU00025## D 1 2 U = AD LR 1 2 U L R T ##EQU00025.2##
[0499] where A.di-elect cons..sup.L.sup.u.sup..times.L.sup.u is a
unitary matrix (i.e AA*=A*A=1), and T.di-elect
cons.(j).sup.L.sup.u.sup..times.L.sup.u is unimodular (i.e. complex
integer entries with determinat 1 or -1). We note that if
M.sub.error is ill-conditioned, then the diagonal of the lattice
reduced Cholesky factor is typically much smaller then the
original. To use the improved Cholesky factorization for THP we
need to make use of two important properties of unimodular
matrices: [0500] If T is unimodular, then T.sup.-1 is also
unimodular. [0501] If v.di-elect cons.(+j).sup.L.sup.u, then
Tv.di-elect cons.(+j).sup.L.sup.u. We now return to the
perturbation problem, where we are trying to find a coarse
perturbation vector v.di-elect cons.(2+2 j).sup.L.sup.u which
minimizes the expected error energy:
[0501] min v ( x + v ) * U * DU ( x + v ) = min v ( x + v ) * ( D 1
2 U ) * ( D 1 2 U ) ( x + v ) = min v ( x + v ) * ( A D LR 1 2 U LR
T ) * A D LR 1 2 U LR T ( x + v ) = min v ( Tx + Tv ) * U LR * D LR
U LR ( T x + Tv ) = min v ~ ( Tx + v .about. ) * U L R * D L R U L
R ( T x + v .about. ) ##EQU00026##
where the last equality follows from the fact that applying
unimodular matrices to coarse perturbation vectors returns coarse
perturbation vectors. THP can now be used to find a coarse
perturbation vector 17 which makes (Tx+{tilde over
(v)})*U.sub.LR*D.sub.LRU.sub.LR (Tx+{tilde over (v)}) small.
Applying T.sup.-1 to {tilde over (v)} returns a coarse perturbation
vector v which makes (x+v)*U*DU(x+v) small. We now summarize the
steps: 1. Compute a lattice reduced Cholesky factorization
U.sub.LR*D.sub.LRU.sub.LR(The most popular algorithm for this is
Lenstra-Lenstra-Lovasz basis reduction). The algorithm will return
the reduced Cholesky factorization and the unimodular matrix T. 2.
Use THP to find a coarse perturbation vector {tilde over (v)} which
makes the equation (1.) small:
(Tx+{tilde over (v)})*U.sub.LR.sup.*D.sub.LRU.sub.LR(Tx+{tilde over
(v)}) (1.)
3. Return T.sup.-1{tilde over (v)}.
[0502] OTFS Tomlinson Harashima Precoding Filters
[0503] This section details of techniques of efficiently computing
coarse OTFS perturbation using a THP filter in the OTFS domain.
[0504] Review of OTFS Perturbation
The goal of OTFS perturbation is to find a coarse perturbation
signal which makes the expected error energy small, where:
expected error energy = f = 0 N f - 1 t = 0 N t - 1 ( X ( f , t ) +
P ( f , t ) ) * M error ( f , t ) ( X ( f , t ) + P ( f , t ) )
##EQU00027##
[0505] Recall that X=.sub.TFx and P=.sub.TFp, where .sub.TF denotes
the two-dimensional Fourier transform, x is the QAM signal, and p
is the perturbation signal. The presence of the Fourier transform
means that perturbing a single QAM in the delay-Doppler domain
affects the signal over the entire time-frequency domain
(illustrated in FIG. 58).
The time-frequency (TF) non-locality of OTFS perturbations carries
advantages and disadvantages. [0506] Advantage: OTFS perturbations
can shape the TF spectrum of the signal to avoid TF channel fades.
[0507] Disadvantage: the OTFS perturbations are typically computed
jointly, this contrasts with OFDM which can compute independent
perturbations for each TF bin.
[0508] When OTFS perturbations are computed jointly, this means
that brute force methods may not work efficiently. For example,
consider the system parameters summarized in Table 7.
TABLE-US-00007 TABLE 7 Typical system parameters N.sub.f 600
N.sub.t 14 L.sub.u 4
[0509] For such a system the space of coarse perturbation signals,
(2+2j).sup.L.sup.u.sup.N.sup.f.sup.N.sup.t, is 3.36e4
dimensional.
[0510] OTFS THP Filters
[0511] To manage the complexity of OTFS perturbations it may be
recalled that the channel is localized in the delay-Doppler domain.
Utilizing this fact, a near optimal coarse perturbation can be
computed using a two-dimensional filter whose length is roughly
equal to the delay and Doppler span of the channel. We call this
class of filters OTFS THP filters. These filters can get quite
sophisticated, so the document will develop them in stages:
starting with simple cases and ending in full generality.
[0512] 1) SISO single carrier (this is equivalent to OTFS with
N.sub.t=1)
[0513] 2) SISO OTFS
[0514] 3) MIMO single carrier
[0515] 4) MIMO OTFS
[0516] SISO Single Carrier
In this section, we disclose a SISO single carrier THP filter.
Towards this end we express the expected error energy in the delay
domain (the domain where QAMs and perturbations are defined):
expected error energy = f = 0 N f - 1 ( X ( f ) + P ( f ) ) * M
error ( f ) ( X ( f ) + P ( f ) ) = .tau. = 0 N .tau. - 1 ( x (
.tau. ) + p ( .tau. ) ) * .tau. ' = 0 N .tau. - 1 m error ( .tau. -
.tau. ' ) ( x ( .tau. ' ) + p ( .tau. ' ) ) ##EQU00028##
The QAM signal x and the perturbation signal p can be represented
as vectors in .sup.N.sup..tau. which we denote by x, p
respectively. Likewise, convolution by m.sub.error can be
represented as multiplication by a positive definite circulant
matrix in .sup.N.sup..tau..sup..times.N.sup..tau. which we denote
by m.sub.error. Using these representations, we can write the
expected error energy as:
expected error energy=(x+p)*m.sub.error(x+p)
[0517] Similar to the spatial case, a good coarse perturbation
vector can be computed (FIG. 59) by utilizing the Cholesky factors
of m.sub.error:
m.sub.error=UDU*
Although the method computes good perturbations, there are two main
challenges: it requires a very large Cholesky factorization and the
application of U-I can be very expensive. To resolve these issues,
we will utilize U.sup.-1 which has much better structure: [0518]
U.sup.-1 is bandlimited, with bandwidth approximately equal to the
channel delay span. [0519] Apart from its edges, U.sup.-1 is nearly
Toeplitz.
[0520] These facts enable the computation of good perturbations
using a short filter which we call the SISO single carrier THP
filter and denote by W.sub.THP. Before showing how to compute
coarse perturbations with U.sup.-1 and W.sub.THP, we illustrate the
structure of U.sup.-1 with a small simulation (parameters in Table
8).
TABLE-US-00008 TABLE 8 Sample rate 10 MHz Number of samples 512
Delay span 3 us Shaping filter Root raised cosine, roll-off 12%
Data noise variance -35 dB Channel noise variance -35 dB
[0521] FIG. 60 displays an estimate of the channel impulse
response. Using this estimate, the error metric in the delay
domain, m.sub.error, was computed. FIG. 61 compares the structure
of the resulting Cholesky factor and its inverse.
[0522] To visualize the near Toeplitz structure of U.sup.-1 we
overlay plots of columns slices (FIG. 45):
s.sub.n(m)=U.sup.-1(n-m,n)
[0523] for m=0, 1, . . . , 40 and n=40, . . . , (N.sub.f-40). We
note that if a matrix is Toeplitz then the slices will be
identical.
[0524] FIG. 62 shows the bandwidth of U.sup.-1 is approximately
equal to the channel span, and that outside of edges the matrix is
very near Toeplitz.
[0525] Computing Good Perturbations with U.sup.-1
In this subsection, we disclose how to compute good perturbations
using U.sup.-1. Towards this end we express the expected error
energy in terms of the Cholesky factors:
expected error energy = ( x + p ) * m error ( x + p ) = ( U ( x + p
) ) * D ( U ( x + p ) ) = z * Dz = .tau. = 0 N .tau. - 1 D ( .tau.
) z ( .tau. ) 2 ##EQU00029##
where z=U(x+p) and D(.tau.)=D(.tau.,.tau.). Therefore, minimizing
the expected error energy is equivalent to minimizing the energy of
the entries of z, which can be expressed recursively:
z ( .tau. ) = x ( .tau. ) + p ( .tau. ) - .tau. ' = .tau. + 1 N
.tau. - 1 U - 1 ( .tau. , .tau. ' ) z ( .tau. ' ) ##EQU00030##
for r=0, 1, . . . , N.sub..tau.-1. Using this expression, a good
perturbation vector can be computed iteratively in the following
way: [0526] 1. Initialization set p(N.sub..tau.-1)=0 and
z(N.sub..tau.-1)=x(N.sub..tau.-1). [0527] 2. Update suppose we have
selected p(.tau.') and z(.tau.') for .tau.'=(.tau.+1), . . . ,
N.sub..tau.-1, then:
[0527] r ( .tau. ) = x ( .tau. ) - .tau. ' = .tau. + 1 N .tau. - 1
U - 1 ( .tau. , .tau. ' ) z ( .tau. ' ) ##EQU00031## p ( .tau. ) =
- ( 2 + 2 j ) ( r ( .tau. ) ) ##EQU00031.2## z ( .tau. ) = x (
.tau. ) + r ( .tau. ) ##EQU00031.3##
[0528] Herein, denotes projection onto the coarse lattice. We note
that the algorithm bounds the energy of the z entries by two. FIG.
63 displays a block diagram of the algorithm.
[0529] Computing Perturbations with W.sub.THP
In this subsection, we disclose how to efficiently compute a good
perturbation using a SISO single carrier THP filter. Towards this
end we note that due to the banded near Toeplitz structure of
U.sup.-1, the application of I-U.sup.-1 can be well approximated by
the application of a filter (outside of edge effects):
.tau. ' = .tau. + 1 N .tau. - 1 U - 1 ( .tau. , .tau. ' ) z ( .tau.
' ) .apprxeq. n = 1 N chan W THP ( n ) z ( .tau. + n ) ,
##EQU00032##
for .tau.=0, 1, . . . , N.sub..tau.-N.sub.chan-1, where N.sub.chan
denotes the channel width. We call W.sub.THP the SISO single
carrier THP filter with:
W.sub.THP(n)=U.sup.-1(N.sub.chan-n,N.sub.chan),
for n=1, N.sub.chan. To use the approximation, we need to avoid the
non-Toeplitz edge effects of U.sup.-1, this is done by enforcing
the QAM signal x to take the value zero for an initialization
region. Putting everything together gives an efficient method for
computing good perturbation signals:
[0530] Setup compute the filter coefficients: W.sub.THP(n) for n=1,
. . . , N.sub.chan.
[0531] Initialization set function values on the top delay bins
equal to zero:
p(.tau.)=0,x(.tau.)=0, and z(.tau.)=0
[0532] for .tau.=N.sub..tau.-N.sub.chan, . . . , N.sub..tau.-1
[0533] Update suppose we have selected p(.tau.') and z(.tau.') for
.tau.'=(.tau.+1), . . . , N.sub..tau.-1, then:
r ( .tau. ) = x ( .tau. ) - n = 1 N chan W THP ( n ) z ( .tau. + n
) ##EQU00033## p ( .tau. ) = - ( 2 + 2 j ) ( r ( .tau. ) )
##EQU00033.2## z ( .tau. ) = x ( .tau. ) + r ( .tau. )
##EQU00033.3##
[0534] Finalize suppose we have selected p(.tau.) and z(.tau.) for
.tau.'=0, 1, . . . , N.sub..tau.-1. Then we take:
x ( .tau. ) = z ( .tau. ) + n = 1 N chan W THP ( n ) z ( .tau. + n
) ##EQU00034##
[0535] for T=N.sub..tau.-N.sub.chan, . . . , N.sub..tau.-1.
[0536] The finalize step is done to ensure that x+p is equal to the
correlation of {square root over (1+W.sub.THP)} and z. Because
there is no QAM information transmitted in the initialization
region, the finalize step does not overwrite user data. We note
that by using unique word single carrier, the initialization region
can also do the work of the cyclic prefix thus limiting overhead. A
block diagram for the update step is shown in FIG. 64.
[0537] Simulation Results
[0538] Application of the SISO single carrier THP filter was
simulated using the parameters given in Table 9.
TABLE-US-00009 TABLE 9 Sample rate 10 MHz Number of samples 512
Delay span 3 us Shaping filter Root raised cosine, roll-off 12%
Data noise variance -35 dB Channel noise variance -35 dB QAM order
Infinity (uniform in unit box)
[0539] Ten thousand random QAM signals were generated and two
different precoders schemes were applied to the QAM signal: [0540]
1) Regularized zero forcing (rZF) [0541] 2) THP perturbation of the
QAM signal followed by rZF
[0542] FIG. 65 displays the channel frequency response. FIG. 66
compares the SINR experienced by the UE for the two precoding
schemes. We note that the THP perturbed signal has both a high
average SINR and an extremely stable SINR. In contract, just using
the linear precoder results in large SINR fluctuations
(20+dBs).
[0543] SISO OTFS
In this section, we disclose SISO OTFS THP filters. The filters
will be intimately related to the previously disclosed SISO single
carrier THP filters. To make the connection clear we represent the
expected error energy in the hybrid delay-time domain.
expected error energy = f = 0 N f - 1 t = 0 N t - 1 ( X ( f , t ) +
P ( f , t ) ) * M error ( f , t ) ( X ( f , t ) + P ( f , t ) ) = t
= 0 N t - 1 .tau. = 0 N .tau. - 1 ( X .about. ( .tau. , t ) + P
.about. ( .tau. , t ) ) * .tau. ' = 0 N .tau. - 1 M ~ error ( .tau.
- .tau. ' , t ) ( X .about. ( .tau.' , t ) + P .about. ( .tau. ' ,
t ) ) , ##EQU00035##
Where the function {tilde over (X)}(.tau.,t) is defined as:
X .about. ( .tau. , t ) = ( F - 1 X .about. ) ( .tau. , t ) f = 0 N
f - 1 e 2 .pi. jf .tau. N f X ( f , t ) ##EQU00036##
and .sub.F.sup.-1 denotes the Fourier transform converting
frequency-time to delay-time. The functions {tilde over (P)}(.tau.,
t) and {tilde over (M)}.sub.error (.tau., t) are defined in the
same way. Next, we vectorize the functions {tilde over (P)}(,t) and
{tilde over (X)}(, t) to express the expected error energy using
linear algebra:
expected error energy = t = 0 N t - 1 ( X ~ t + P ~ t ) * M ~ e r r
o r , t ( X ~ t + P ~ t ) ##EQU00037##
where {tilde over (X)}.sub.t, {tilde over (P)}.sub.t .di-elect
cons..sup.N.sup..tau. and the matrices {tilde over (M)}.sub.error,t
.di-elect cons..sup.N.sup..tau..sup..times.N.sup..tau. are
circulant and positive definite.
[0544] Computing Perturbations with U.sup.-1
In this subsection, we disclose how to compute good perturbations
using the Cholesky decompositions:
{tilde over (M)}.sub.error,t= .sub.t.sup.*{tilde over (D)}.sub.t
.sub.t,
for t=0, 1, . . . , N.sub..tau.-1. Where the .sub.t are unit upper
triangular and the {tilde over (D)}.sub.t are positive diagonal.
Expressing the expected error energy in terms of these
decompositions gives:
expected error energy = t = 0 N t - 1 ( X ~ t + P t ) * U ~ t * D ~
t U ~ t ( X ~ t + P ~ t ) = t = 0 N t - 1 Z ~ t * D ~ t Z ~ t =
.tau. = 0 N .tau. - 1 t = 0 N t - 1 Z .about. ( .tau. , t ) * D ~ (
.tau. , t ) Z .about. ( .tau. , t ) ##EQU00038##
where {tilde over (Z)}.sub.t= .sub.t({tilde over (X)}.sub.t+{tilde
over (P)}.sub.t), {tilde over (Z)}(.tau., t)={tilde over
(Z)}.sub.t(.tau.), and {tilde over (D)}(.tau.,t)={tilde over
(D)}.sub.t(.tau.,.tau.). Next, we express the expected error energy
in the delay-Doppler domain (the domain where the QAMs and
perturbations are defined):
expected error energy = .tau. = 0 N .tau. - 1 v = 0 N v - 1 z (
.tau. , v ) * v ' = 0 N v - 1 d ( .tau. , v - v ' ) z ( .tau. , v '
) ##EQU00039##
where the function z(.tau., v) is defined as:
z ( .tau. , v ) = ( T - 1 Z .about. ) ( .tau. , v ) = t = 0 N t - 1
e 2 .pi. jtv N t Z ~ ( .tau. , t ) ##EQU00040##
and .sub.T.sup.-1 denotes the Fourier transform converting
delay-time to delay-Doppler. The function d(.tau.,.nu.) is defined
the same way. For Doppler shifts encountered in typical wireless
channels (.ltoreq.500 Hz) the term {tilde over (D)}(.tau., t) is
nearly constant with respect to time. Therefore, the energy of its
Fourier transform, d(.tau.,.nu.), will be concentrated in the DC
term, d(.tau., 0). Using this fact, the expected error energy can
be well approximated as:
expected error energy .apprxeq. .tau. = 0 N .tau. - 1 v = 0 N v - 1
z ( .tau. , v ) * d ( .tau. , 0 ) z ( .tau. , v ) = .tau. = 0 N
.tau. - 1 v = 0 N v - 1 d ( .tau. , 0 ) z ( .tau. , v ) 2
##EQU00041##
Because the terms d(.tau., 0) are positive, minimizing the expected
error energy is equivalent to minimizing the energy of the entries
of z, which can be expressed recursively:
Z ~ ( .tau. , t ) = X ~ ( .tau. , t ) + P ~ ( .tau. , t ) - .tau. '
= .tau. + 1 N .tau. - 1 U ~ t - 1 ( .tau. , .tau. ' ) Z ~ ( .tau. '
, t ) ##EQU00042## z ( .tau. , v ) = x ( .tau. , v ) + p ( .tau. ,
v ) - T - 1 ( .tau. ' = .tau. + 1 N .tau. - 1 U ~ t - 1 ( .tau. ,
.tau. ' ) Z ~ ( .tau. ' , t ) ) ( .tau. , v ) ##EQU00042.2##
[0545] Using these expressions, a good perturbation signal can be
computed iteratively:
Initialization set {tilde over (P)}(N.sub..tau., t)=0 and {tilde
over (Z)}(N.sub..tau.,t)={tilde over (X)}(N.sub..tau.,t) for t=0,
1, . . . , N.sub..tau.-1 Update suppose we have selected {tilde
over (P)}(.tau.', t) and {tilde over (Z)}(.tau.',t) for
.tau.'=(.tau.+1), . . . , N.sub..tau.-1, then:
R .about. ( .tau. , t ) = X .about. ( .tau. , t ) .tau. = .tau. + 1
N .tau. - 1 U ~ t - 1 ( .tau. , .tau. ' ) Z ~ ( .tau. ' , t )
##EQU00043## p ( .tau. , v ) = - ( 2 + 2 j ) ( ( T - 1 R .about. )
( .tau. , v ) ) ##EQU00043.2## P .about. ( .tau. , t ) = ( t p ) (
.tau. , t ) ##EQU00043.3## Z .about. ( .tau. , t ) = P .about. (
.tau. , t ) + R .about. ( .tau. , t ) ##EQU00043.4##
for t=0, 1, . . . , N.sub.t-1, where denotes projection onto the
coarse lattice. We note that the algorithm bounds the energy of the
entries of z by two. FIG. 67 displays a block diagram of the
algorithm.
[0546] Computing Perturbations with W.sub.THP
In this subsection we disclose how to compute good perturbations
using SISO OTFS THP filters. Exactly like the single carrier case,
the application of I- .sup.-1 can be well approximated by the
application of a filter (outside of edge effects):
.tau. ' = .tau. + 1 N .tau. - 1 U ~ t - 1 ( .tau. , .tau. ' ) z (
.tau. ' , t ) .apprxeq. n = 1 N c h a n W T H P ( n , t ) z ( .tau.
+ n , t ) , ##EQU00044##
for .tau.=0, 1, . . . , N.sub..tau.-N.sub.chan and t=0, 1, . . . ,
N.sub.t-1, where N.sub.chan denotes the channel delay width. We
call the filters W.sub.THP(,t) the SISO OTFS THP filters with:
W.sub.THP(n,t)= .sub.T.sup.-1(N.sub.chan-n,N.sub.chan),
for .tau.=0, 1, . . . , N.sub.t-1 and n=1, . . . , N.sub.chan. Like
the single carrier case, to avoid edge effects, we enforce the QAM
signal x to take the value zero in an initialization region.
Putting everything together gives an efficient method to compute
good perturbations: [0547] 1. Setup compute the filter
coefficients: W.sub.THP (n,t) for t=0, 1, . . . , N.sub.t-1 and
n=1, . . . , N.sub.chan. [0548] 2. Initialization set function
values on the top delay bins equal to zero:
[0548] {tilde over (P)}(.tau.,t)=0,{tilde over (X)}(.tau.,t)=0, and
{tilde over (Z)}(.tau.,t)=0, [0549] for
.tau.=N.sub..tau.-N.sub.chan, . . . , N.sub..tau.-1 and t=0, 1, . .
. , N.sub.t-1. [0550] 3. Update Suppose we have selected {tilde
over (P)}(.tau.',t) and {tilde over (Z)}(.tau.', t) for
.tau.'=(.tau.+1), . . . , N.sub..tau.-1 and t=0, 1, . . . ,
N.sub.t-1, then:
[0550] R ~ ( .tau. , t ) = X .about. ( .tau. , t ) - n = 1 N c h a
n W T H P ( n , t ) Z .about. ( .tau. + n , t ) ##EQU00045## p (
.tau. , v ) = - ( 2 + 2 j ) ( ( T - 1 R .about. ) ( .tau. , v ) )
##EQU00045.2## P .about. ( .tau. , t ) = ( t p ) ( .tau. , t )
##EQU00045.3## Z .about. ( .tau. , t ) = X .about. ( .tau. , t ) +
R .about. ( .tau. , t ) ##EQU00045.4## [0551] for t=0, 1, . . .
,N.sub.t-1 and .nu.=0, 1, . . . , N.sub..nu.-1. [0552] 4. Finalize
suppose we have selected {tilde over (Z)}(.tau.', t) and {tilde
over (P)}(.tau.', t) for .tau.'=0, 1, . . . , N.sub..tau.-1 and
t=0, 1, . . . , N.sub.t-1. Then we take:
[0552] X .about. ( .tau. , t ) = Z .about. ( .tau. , t ) + n = 1 N
c h a n W T HP , t ( n ) Z .about. ( .tau. , t ) ##EQU00046##
[0553] for .tau.=N.sub..tau.-N.sub.chan, . . . , N.sub..tau.-1 and
t=0, 1, . . . , N.sub.t-1.
[0554] Because there is no QAM information transmitted in the
initialization region the finalize step does not overwrite user
data. We note that by using unique word OTFS, the initialization
region can also do the work of the cyclic prefix thus limiting
overhead. A block diagram for the update step is shown in FIG.
68.
[0555] Simulation Results
[0556] Application of the SISO OTFS THP filters was simulated using
the parameters given in Table 10.
TABLE-US-00010 TABLE 10 Sample rate 10 MHz N.sub.f, N.sub..tau. 128
N.sub.t, N.sub..nu. 64 Delay span 1 us Doppler span 1 kHz Shaping
filter Root raised cosine, roll-off 12% Data noise variance -35 dB
Channel noise variance -35 dB QAM order Infinity (uniform in unit
box)
[0557] FIG. 69 displays the channel time frequency response. FIG.
70 compares the SINR experienced by the UE for the two precoding
schemes. We note that the THP perturbed signal has both a high
average SINR and an extremely stable SINR. In contract, just using
the linear precoder results in large SINR fluctuations
(20+dBs).
[0558] MIMO Single Carrier
In this section, we disclose a MIMO single carrier THP filter. The
filter will be like the SISO single carrier THP filter, however,
with the filter taps now being matrix valued instead of scaler
valued. Towards this end we express the expected error energy in
the delay domain (the domain where QAMs and perturbations are
defined):
expected error energy = f = 0 N f - 1 ( X ( f ) + P ( f ) ) * M
error ( f ) ( X ( f ) + P ( f ) ) = .tau. = 0 N .tau. - 1 ( x (
.tau. ) + p ( .tau. ) ) * .tau. ' = 0 N .tau. - 1 m error ( .tau. -
.tau. ' ) ( x ( .tau. ' ) + p ( .tau. ' ) ) ##EQU00047##
where x(.tau.), p(.tau.).di-elect cons..sup.L.sup.u and
m.sub.error(.tau.).di-elect cons..sup.L.sup.u.sup..times.L.sup.u.
The QAM signal x and the perturbation signal p can be represented
as vectors in .sup.L.sup.u.sup.N.sup.T, which we denote by x, p
respectively. Likewise, convolution by m.sub.error can be
represented as multiplication by a positive definite block
circulant matrix in
.sup.L.sup.u.sup.N.sup..tau..sup..times.L.sup.u.sup.N.sup..tau.
(blocks are of size L.sub.u.times.L.sub.u) which we denote by
m.sub.error Using these representations, we can write the expected
error energy as:
expected error energy=(x+p)*m.sub.error(x+p)
[0559] Computing Perturbations with Block Cholesky Factors
In this subsection, we disclose how to compute good perturbations
using the block Cholesky decomposition:
m.sub.error=U*DU,
where D is positive definite block diagonal and U is block unit
upper triangular (i.e. upper triangular with block diagonal
matrices equal to the identity matrix). Expressing the expected
error energy in terms of the Cholesky factors gives:
expected error energy = ( U ( x + p ) ) * D ( U ( x + p ) ) = z *
Dz = .tau. = 0 N .tau. - 1 z ( .tau. ) * D ( .tau. ) z ( .tau. )
##EQU00048##
with: [0560] z=U(x+p) [0561] z(.tau.) .di-elect cons..sup.L.sup.u
equal to the spatial values of z at delay bin .tau.:
[0561] z(.tau.)=z(.tau.L.sub.u:(.tau.+1)L.sub.u-1)
[0562] D(.tau.).di-elect cons..sup.L.sup.u.sup..times.L.sup.u equal
to the .tau.'th block diagonal entry of D:
D(.tau.)=D(.tau.L.sub.u:(.tau.+1)L.sub.u-1,.tau.L.sub.u:(.tau.+1)L.sub.u-
-1)
Therefore, minimizing the expected error energy is equivalent to
minimizing the quadratic forms z(.tau.)*D(.tau.)z(.tau.), where the
value of z(.tau.) can be expressed recursively:
z ( .tau. ) = x ( .tau. ) + p ( .tau. ) - .tau. ' = .tau. + 1 N
.tau. - 1 U - 1 ( .tau. , .tau. ' ) z ( .tau. ' ) ##EQU00049##
with: [0563] x(.tau.).di-elect cons..sup.L.sup.u equal to the
spatial values of x at delay bin .tau.:
[0563] x(.tau.)=x(.tau.L.sub.u:(.tau.+1)L.sub.u-1) [0564]
p(.tau.).di-elect cons..sup.L.sup.u equal to the spatial values of
p at delay bin .tau.:
[0564] p(.tau.)=p(.tau.L.sub.u:(.tau.+1)L.sub.u-1) [0565]
U.sup.-1(.tau.,.tau.').di-elect
cons..sup.L.sup.u.sup..times.L.sup.u equal to the (.tau.,.tau.')
block entry of U.sup.-1:
[0565]
U.sup.-1(.tau.,.tau.')=U.sup.-1(.tau.L.sub.u:(.tau.+1)L.sub.u-1,.-
tau.'L.sub.u:(.tau.'+1)L.sub.u-1)
Suppose the value of z(.tau.') has been selected for
.tau.'=(.tau.+1), . . . , N.sub..tau.-1, then the problem of
minimizing the quadratic form z(.tau.)*D(.tau.)z(.tau.) can be cast
as a closest lattice point problem (CLP) by noting that:
z ( .tau. ) * D ( .tau. ) z ( .tau. ) = ( r ( .tau. ) + p ( .tau. )
) * D ( .tau. ) ( r ( .tau. ) + p ( .tau. ) ) r ( .tau. ) = x (
.tau. ) - .tau. ' = .tau. + 1 N .tau. - 1 U - 1 ( .tau. , .tau. ' )
z ( .tau. ' ) ##EQU00050##
Therefore, minimizing the quadratic form is equivalent to solving
the CLP:
argmin p .di-elect cons. ( 2 + 2 j ) L u ( r ( .tau. ) + p ) * D (
.tau. ) ( r ( .tau. ) + p ) ( 1 ) ##EQU00051##
In general, the CLP problem is NP hard. A quick but suboptimal
solution can be computed by projecting each coordinate of -r(.tau.)
onto the lattice 27+2j:
P(i)=-(r(.tau.))(i)
for i=0, . . . , L.sub.u-1. To compute a better solution a form of
spatial THP should be used; this includes the methods of V-Blast,
sphere-encoding, k-best, lattice reduction, and their variants.
Putting everything together gives a method to iteratively compute
good perturbation signals: [0566] 1. Initialization set
p(N.sub..tau.)=0 and z(N.sub..tau.)=x(N.sub..tau.). [0567] 2.
Update Suppose we have selected p(.tau.') and z(.tau.') for
.tau.'=(.tau.+1), . . . , N.sub..tau.-1, then:
[0567] r ( .tau. ) = x ( .tau. ) - .tau. ' = .tau. + 1 N .tau. - 1
U - 1 ( .tau. , .tau. ' ) z ( .tau. ' ) ##EQU00052## p ( .tau. ) =
C L P D ( .tau. ) ( r ( .tau. ) ) ##EQU00052.2## z ( .tau. ) = p (
.tau. ) + r ( .tau. ) ##EQU00052.3## [0568] where
CLP.sub.D(.tau.)(r(.tau.)) denotes some (usually suboptimal)
solution to the CLP problem of equation 1. A block diagram for the
update step is shown in FIG. 71.
[0569] Computing Perturbations with W.sub.THP
In this subsection we disclose how to compute good perturbations
using a MIMO single carrier THP filter. Like the SISO case, the
application of I-U.sup.-1 can be well approximated by the
application of a filter (outside of edge effects):
.tau. ' = .tau. + 1 N .tau. - 1 U - 1 ( .tau. , .tau. ' ) z ( .tau.
' ) .apprxeq. n = 1 N c h a n W T H P ( n ) z ( .tau. + n ) ,
##EQU00053##
for .tau.=0, 1, . . . , N.sub..tau.-N.sub.chan-1, where N.sub.chan
denotes the width of the channel. We call the filter W.sub.THP the
MIMO single carrier THP filter with:
W.sub.THP(n).di-elect cons..sup.L.sup.u.sup..times.L.sup.u and
W.sub.THP(n)=U.sup.-1(N.sub.chan-n,N.sub.chan),
for n=1, . . . , N.sub.chan. Also, outside of edge effects the
positive definite matrix D(.tau.) is nearly constant:
D(.tau.).apprxeq.D(N.sub.chan),
for .tau.=N.sub.chan, . . . , N.sub..tau.-N.sub.chan-1. To avoid
edge effects we enforce the QAM signal, x, to be zero for an
initialization region. Putting everything together gives an
efficent method to compute coarse perturbations: [0570] 1. Setup
compute the filter coefficients W.sub.THP (n) for n=1, . . . ,
N.sub.chan Compute the positive definite matrix D(N.sub.chan).
[0571] 2. Initialization set the function values on the top delay
bins equal to zero:
[0571] p(.tau.)=0,x(.tau.)=0, and z(.tau.)=0, [0572] for
.tau.=N.sub..tau.-N.sub.chan, . . . , N.sub..tau.-1. [0573] 3.
Update Suppose we have selected p(.tau.') and z(.tau.') for
.tau.'=(.tau.+1), . . . , N.sub..tau.-1, then:
[0573] r ( .tau. ) = x ( .tau. ) - n = 1 N chan W THP ( n ) z (
.tau. + n ) ##EQU00054## p ( .tau. ) = C L P D ( N chan ) ( r (
.tau. ) ) ##EQU00054.2## z ( .tau. ) = p ( .tau. ) + r ( .tau. )
##EQU00054.3## [0574] 4. Update suppose we have selected p(.tau.')
and z(.tau.') for .tau.'=0, 1, . . . , N.sub..tau.-1. Then we
take:
[0574] x ( .tau. ) = z ( .tau. ) + n = 1 N c h a n W THP ( n ) z (
.tau. + n ) , ##EQU00055## [0575] for T=N.sub..tau.-N.sub.chan, . .
. , N.sub..tau.-1.
[0576] Because there is no QAM information transmitted in the
initialization region the finalize step does not overwrite user
data. We note that by using unique word single carrier, the
initialization region can also do the work of the cyclic prefix
thus limiting overhead. A block diagram for the update step is
shown in FIG. 72.
[0577] Simulation Results
[0578] Application of the MIMO single carrier THP filter was
simulated with the parameters given in Table 11.
TABLE-US-00011 TABLE 11 Subcarrier spacing 15 kHz N.sub.f,
N.sub..tau. 600 Delay span 2 us Doppler span 0 kHz Data noise
variance -35 dB Channel noise variance -35 dB L.sub.u 8 L.sub.h 8
QAM order Infinity (uniform in unit box)
[0579] FIG. 73 compares the SINR experienced by the 8 UEs for the
two precoding schemes. We note that the THP perturbed signal has
both a high average SINR and an extremely stable SINR. In contrast,
just using the linear precoder results in large SINR fluctuations
(20+dB s).
[0580] MIMO OTFS
In this section, we disclose MIMO OTFS THP filters. The filters
will be like the SISO OTFS THP filters, however, with the filter
taps now being matrix valued instead of scaler valued. Towards this
end we express the expected error energy in the hybrid delay-time
domain:
expected error energy = f = 0 N f - 1 t = 0 N t - 1 ( X ( f , t ) +
P ( f , t ) ) * M error ( f , t ) ( X ( f , t ) + P ( f , t ) ) = t
= 0 N t - 1 .tau. = 0 N .tau. - 1 ( X ~ ( .tau. , t ) + P ~ ( .tau.
, t ) ) * .tau. ' = 0 N .tau. - 1 M ~ error ( .tau. - .tau. ' , t )
( X ~ ( .tau. ' , t ) + P ~ ( .tau. ' , t ) ) , ##EQU00056##
Where the function {tilde over (X)}(.tau., t) is defined as:
X ~ ( .tau. , t ) = ( F - 1 X ) ( .tau. , t ) = f = 0 N f - 1 e 2
.pi. j f .tau. N f X ( f , t ) ##EQU00057##
The functions {tilde over (P)}(.tau.,t) and M.sub.error (.tau., t)
are defined in the same way. Next, we vectorize the functions
{tilde over (P)}(,t) and {tilde over (X)}(,t) to express the
expected error energy using linear algebra:
expected error energy = t = 0 N t - 1 ( X ~ t + P ~ t ) * M ~ e r r
o r , t ( X ~ t + P ~ t ) ##EQU00058##
where {tilde over (X)}.sub.t, {tilde over (P)}.sub.t .di-elect
cons..sup.L.sup.u.sup.N.sup.t and the matrices {tilde over
(M)}.sub.error,t .di-elect
cons..sup.L.sup.u.sup.N.sup..tau..sup..times.L.sup.u.sup.N.sup..tau.
are positive definite and block circulant (with blocks of size
L.sub.u.times.L.sub.u).
[0581] Computing Perturbations with Block Cholesky Factors
In this subsection, we disclose how to compute good perturbations
using the block Cholesky decompositions:
{tilde over (M)}.sub.error,t= .sub.t.sup.*{tilde over (D)}.sub.t
.sub.t,
for t=0, 1, . . . , N.sub.t-1, where the {tilde over (D)}.sub.t are
positive definite block diagonal and the .sub.t are block unit
upper triangular (i.e. upper triangular with block diagonal
matrices equal to the identity matrix). Expressing the expected
error energy in terms of these Cholesky factors gives:
expected error energy = t = 0 N t - 1 ( X ~ t + P ~ t ) * U ~ t * D
~ t U ~ t ( X ~ t + P ~ t ) = t = 0 N t - 1 Z ~ t * D ~ t Z ~ t =
.tau. = 0 N .tau. - 1 L = 0 N t - 1 Z ~ ( .tau. , t ) * D ~ ( .tau.
, t ) Z ~ ( .tau. , t ) , ##EQU00059##
with:
[0582] {tilde over (Z)}= .sub.t({tilde over (X)}.sub.t+{tilde over
(P)}.sub.t)
[0583] {tilde over (Z)}(.tau., t).di-elect cons..sup.L.sup.u equal
to the spatial values of {tilde over (Z)}.sub.t at delay bin
.tau.:
{tilde over (Z)}(.tau.,t)={tilde over
(Z)}.sub.t(.tau.L.sub.u:(.tau.+1)L.sub.u-1) [0584] {tilde over
(D)}(.tau.,t).di-elect cons..sup.L.sup.u.sup..times.L.sup.u equal
to the .tau.'th block diagonal entry of {tilde over (D)}.sub.t:
[0584] {tilde over (D)}(.tau.,t)={tilde over
(D)}.sub.t(.tau.L.sub.u:(.tau.+1)L.sub.u-1,.tau.L.sub.u:(.tau.+1)L.sub.u--
1)
Next, we express the expected error energy in the delay-Doppler
domain (the domain where QAMs and perturbations are defined):
expected error energy = .tau. = 0 N .tau. - 1 v = 0 N v - 1 z (
.tau. , v ) * v ' = 0 N v - 1 d ( .tau. , v - v ' ) z ( .tau. , v '
) ##EQU00060##
where the function z(.tau.,.nu.) is defined as:
z ( .tau. , v ) = ( T - 1 Z ~ ) ( .tau. , v ) = t = 0 N t - 1 e 2
.pi. j tv N t Z ~ ( .tau. , t ) ##EQU00061##
The function d(.tau.,.nu.) is defined in the same way. For Doppler
shifts encountered in typical wireless channels (.ltoreq.500 Hz)
the term {tilde over (D)}(.tau., t) is nearly constant with respect
to time, therefore, the energy of its inverse Fourier transform,
d(.tau.,.nu.), is concentrated in the DC term, d(.tau., 0). Using
this fact, the expected error energy can be well approximated
as:
expected error energy .apprxeq. .tau. = 0 N .tau. - 1 v = 0 N v - 1
z ( .tau. , v ) * d ( .tau. , 0 ) z ( .tau. , v ) ##EQU00062##
In conclusion, minimizing the expected error energy is equivalent
to minimizing the quadratic forms z(.tau.,.nu.)*d(.tau., 0)z
(.tau., v), where the value of z(.tau.,.nu.) can be expressed
recursively:
z ( .tau. , v ) = x ( .tau. , v ) + p ( .tau. , v ) - T - 1 ( .tau.
' = .tau. + 1 N .tau. - 1 U ~ t - 1 ( .tau. , .tau. ' ) Z ~ ( .tau.
' , t ) ) ( .tau. , v ) ##EQU00063##
with: [0585] x(.tau.,.nu.).di-elect cons..sup.L.sup.u equal to the
spatial values of x at delay-Doppler bin (.tau.,.nu.) [0586]
p(.tau.,.nu.).di-elect cons..sup.L.sup.u equal to the spatial
values of p at delay-Doppler bin (.tau.,.nu.) [0587]
.sub.t.sup.-1(.tau.,.tau.').di-elect
cons..sup.L.sup.u.sup..times.L.sup.u equal to the (.tau., .tau.')
block entry of .sub.t.sup.-1:
[0587] .sub.t.sup.-1(.tau.,.tau.')=
.sub.T.sup.-1(.tau.L.sub.u:(.tau.+1)L.sub.u-1,.tau.'L.sub.u:(.tau.'+1)L.s-
ub.u-1)
Suppose the value of {tilde over (Z)}(.tau.', t) has been selected
for .tau.'=(.tau.+1), . . . , N.sub..tau.-1 and t=0, 1, . . . ,
N.sub.t-1, then the problem of minimizing the quadradic forms
z(.tau.,.nu.)*d(.tau.,0)z(.tau.,.nu.) can be cast as a closest
lattice point problem (CLP) by noting that:
z ( .tau. , v ) * d ( .tau. , 0 ) z ( .tau. ) = ( r ( .tau. , v ) +
p ( .tau. , v ) ) * d ( .tau. , 0 ) ( r ( .tau. , v ) + p ( .tau. ,
v ) ) ##EQU00064## r ( .tau. , v ) = x ( .tau. , v ) - T - 1 (
.tau. ' = .tau. + 1 N .tau. - 1 U ~ t - 1 ( .tau. , .tau. ' ) Z ~ (
.tau. ' , t ) ) ( .tau. , v ) ##EQU00064.2##
Therefore, minimizing the quadratic form is equivalent to solving
the CLP:
arg min p .di-elect cons. ( 2 + 2 j ) L u ( r ( .tau. , v ) + p ) *
d ( .tau. , 0 ) ( r ( .tau. , v ) + p ) ( 2 ) ##EQU00065##
In general, the CLP problem is NP hard. A quick but suboptimal
solution can be computed by projecting each coordinate of
r(.tau.,.nu.) onto the lattice 2 +2j:
p(i)=-(r(.tau.,.nu.))(i)
for i=0, 1, . . . , L.sub.u-1. To compute a better solution, a form
of spatial THP should be used; this includes the methods of
V-Blast, sphere-encoding, k-best, lattice reduction, and their
variants. Putting everything together gives a method to iteratively
compute a good perturbation signal: [0588] 1. Initialization set
P(N.sub..tau., t)=0 and {tilde over (Z)}(N.sub..tau., t)={tilde
over (X)}(N.sub..tau., t) for t=0, 1, . . . , N.sub.t-1 [0589] 2.
Update Suppose we have selected {tilde over (P)}(.tau.', t) and
{tilde over (Z)}(.tau.', t) for .tau.'=(.tau.+1) . . .
N.sub..tau.-1, then:
[0589] R ~ ( .tau. , t ) = X ~ ( .tau. , t ) .tau. ' = .tau. + 1 N
.tau. - 1 U ~ t - 1 ( .tau. , .tau. ' ) Z ~ ( .tau. ' , t )
##EQU00066## r ( .tau. , v ) = ( T - 1 R ~ ) ( .tau. , v )
##EQU00066.2## p ( .tau. , v ) = C L P d ( .tau. , 0 ) ( r ( .tau.
, v ) ) ##EQU00066.3## P ~ ( .tau. , t ) = ( T p ) ( .tau. , t )
##EQU00066.4## Z ~ ( .tau. , t ) = P ~ ( .tau. , t ) + R ~ ( .tau.
, t ) ##EQU00066.5##
[0590] here CLP.sub.d(.tau.,0)(r(.tau.,.nu.)) denotes some (usually
suboptimal) solution to the CLP problem of equation 2. FIG. 74
shows a block diagram for the update step.
[0591] Computing Perturbations with W.sub.THP
[0592] In this subsection we disclose how to compute good
perturbations using MIMO OTFS THP filters Like the SISO case, the
application of 1- .sup.-1 can be well approximated by the
application of filters (outside of edge effects):
.tau. ' = .tau. + 1 N .tau. - 1 U ~ t - 1 ( .tau. , .tau. ' ) z (
.tau. ' ) .apprxeq. n = 1 N c h a n W THP ( n , t ) z ( .tau. + n ,
t ) , ##EQU00067##
for .tau.=0, 1, . . . , N.sub..tau.-N.sub.chan-1 and t=0, 1, . . .
, N.sub.t-1, where N.sub.chan denotes the width of the channel. We
call the filters W.sub.THP(,t) the MIMO OTFS THP filters with:
W.sub.THP(n,t).di-elect cons..sup.L.sup.u.sup..times.L.sup.u and
W.sub.THP(n,t)= .sub.t.sup.-1(N.sub.chan-n,N.sub.chan),
for n=1, . . . , N.sub.chan and t=0, 1, . . . ,N.sub.t. Also,
outside of edge effects the positive definite matrix d(.tau.,0) is
nearly constant:
d(.tau.,0)).apprxeq.d(N.sub.chan,0),
for .tau.=N.sub.chan, N.sub..tau.-N.sub.chan-1. To avoid edge
effects we enforce the QAM signal, x, to be zero for an
initialization region. Putting everything together gives an
efficient method to compute good perturbations: [0593] 1. Setup
compute the filter coefficients: W.sub.THP(n,t) for t=0, 1, . . . ,
N.sub.t-1 and n=1, . . . , N.sub.chan. Compute the positive
definite matrix d(N.sub.chan, 0). [0594] 2. Initialization set
function values on the top delay bins equal to zero:
[0594] {tilde over (P)}(.tau.,t)=0,{tilde over (X)}(.tau.,t)=0, and
{tilde over (Z)}(.tau.,t)=0, [0595] for .tau.=N.tau.-N.sub.chan, .
. . , N.sub..tau.-1 and t=0, 1, . . . , N.sub.t-1. [0596] 3. Update
suppose we have selected {tilde over (P)}(.tau.', t) and {tilde
over (Z)}(.tau.', t) for .tau.'=(.tau.+1), . . . , N.sub..tau.-1
and t=0, 1, . . . , N.sub..tau.-1 then:
[0596] R ~ ( .tau. , t ) = X ~ ( .tau. , t ) - n = 1 N c h a n W
THP , t ( n ) Z ~ ( .tau. + n , t ) ##EQU00068## r ( .tau. , v ) =
( T - 1 R ~ ) ( .tau. , v ) ##EQU00068.2## p ( .tau. , v ) = C L P
d ( N c h a n , 0 ) ( r ( .tau. , v ) ) ##EQU00068.3## P ~ ( .tau.
, t ) = ( T p ) ( .tau. , t ) ##EQU00068.4## Z ~ ( .tau. , t ) = X
~ ( .tau. , t ) + R ~ ( .tau. , t ) ##EQU00068.5## [0597] for t=0,
1, . . . ,N.sub.t-1 and v=0, 1, . . . , N.sub..nu.-1. [0598] 4.
Finalize suppose we have selected {tilde over (Z)}(.tau.', t) and
{tilde over (P)}(.tau.', t) for .tau.'=0, 1, . . . , N.sub..tau.-1
and t=0, 1, . . . , N.sub.t-1. Then we take:
[0598] X ~ ( .tau. , t ) = Z ~ ( .tau. , t ) + n = 1 N c h a n W
THP ( n , t ) Z ~ ( .tau. , t ) ##EQU00069## [0599] for
.tau.=N.sub..tau.-N.sub.chan, . . . , N.sub..tau.-1 and t=0, 1, . .
. ,N.sub.t-1.
[0600] Because there is no QAM information transmitted in the
initialization region the finalize step does not overwrite user
data. We note that by using unique word OTFS, the initialization
region can also do the work of the cyclic prefix thus limiting
overhead. A block diagram for the update step is shown in FIG.
75.
[0601] Simulation Results
[0602] Application of the OTFS MIMO THP filter was simulated with
the parameters given in Table 12.
TABLE-US-00012 TABLE 12 Subcarrier spacing 15 kHz N.sub.f,
N.sub..tau. 128 N.sub.t, N.sub..nu. 256 Delay span 1 us Doppler
span 1 kHz Data noise variance -35 dB Channel noise variance -35 dB
L.sub.u 8 L.sub.h 8 QAM order Infinity (uniform in unit box)
[0603] FIG. 76 shows the SINR experienced by UE 1 for the two
precoding schemes. We note that the THP perturbed signal has both a
high average SINR and an extremely stable SINR. In contrast, just
using the linear precoder results in large SINR fluctuations
(15+dBs).
Section 5: Transmitter and Receiver Implementations for OTFS
[0604] In some embodiments, the following design features are
consideration in the implementation of a transmitter and receiver
of an OTFS modulated communication system. [0605] UPLINK: UE
multiplexes users in delay-Doppler using DFT-s-OTFS and BS
equalizes using turbo receiver [0606] Diversity gain [0607] Low
PAPR [0608] Low complexity UE transmitter [0609] Compared to OFDM,
OTFS systems may be able to offer Higher link budget (>7 dB
gain) and simpler UE transmitter (<1/2 complexity) [0610]
DOWNLINK: BS multiplexes users in delay-Doppler and pre-equalizes
using delay-Doppler THP precoding [0611] Delay-Doppler
Tomlinson-Harashima precoding gain [0612] Low complexity UE
receiver [0613] Compared to pre-coded OFDM: Higher MU-MIMO
efficiency (<1/4 # BS antennas) and simpler UE receiver (<1/2
complexity)
[0614] FIGS. 77-81 show various embodiments of transmitter and
receiver architectures that may be used, in conjunction with the
techniques described in Section 1-4. FIG. 77 shows an example of
modulation and demodulation architecture for an OTFS modulated
communication system. FIG. 78 shows an example modulation and
demodulation architecture for a DFT-S OTFS modulated communication
system. FIGS. 79 and 80 show examples of an uplink base station
turbo receiver architecture and a downlink base station transmitter
architecture, respectively. FIG. 81 shows an example block diagram
for downlink channel processing at the base station.
[0615] In some embodiments, the transmitter shown in FIGS. 77-79
may include: [0616] SVD precoding, which can typically be applied
for SU-MIMO in static/slow varying channels, and has the same
performance as OTFS. [0617] MU-MIMO that requires linear precoding
schemes or their non-linear enhancements. For example, linear
precoding schemes include zero-forcing/matched precoders that are
not capacity-achieving, and non-linear precoders include the THP
enhancement which approaches capacity. [0618] The THP enhancement
which can be implemented for both OFDM and OTFS. However, OFDM THP
complexity is exponential and is not capacity-achieving in the
presence of time-frequency selectivity. In contrast, OTFS optimal
THP complexity is quadratic and is always capacity-achieving.
[0619] UE transmitter is lower complexity for standalone OTFS.
[0620] In some embodiments, features of the receiver complexity
include: [0621] For capacity-achieving equalizers, OFDM ML (maximum
likelihood) complexity grows exponentially with MIMO
order/constellation size in the presence of spatial correlations,
and OTFS DFE/Turbo complexity grows quadratically. [0622] For more
than 2.times.2 MIMO, OTFS equalizer typically has lower complexity
than OFDM. [0623] With precoding: standalone OTFS has lower
transmitter & receiver complexity at the UE.
[0624] FIG. 82 shows an example of uplink DFT-S OTFS user
multiplexing. In this example, there are 250 QAM symbols in a
physical resource block (PRB), with 2 beams, and 16 PRBs per beam.
As shown in FIG. 82, there are 5 users (2 user with 4 PRB, 1 users
with 2 PRB, 2 users with 1 PRB) in the first beam and 2 users (2
users with 4 PRB each) in the second beam.
Section 6: Hardware and Antenna Implementations for OTFS
[0625] This section covers hardware and antenna implementations
that may be used in conjunction with the described transmitter and
receiver implementations (Section 5), and include an antenna system
comprising a hemispherical dome (Section 6.1), a variable beamwidth
multiband antenna (Section 6.2), SWAP (size, weight and power)
optimized devices (Section 6.3), and light bulbs with integrated
antennas (Section 6.4).
6.1 Antenna System with a Hemispherical Dome
[0626] FIG. 83 shows an example of a fixed wireless access system.
A hub, that includes a transmission facility such as a cell tower,
is configured to send and receive transmissions to/from multiple
locations. For example, the locations could be user premises or
business buildings. As described throughout this document, the
disclosed techniques can achieve very high cell capacity fixed
wireless access, when compared to traditional fixed access
technology. In one advantageous aspect, the transmissions may be
performed on a relatively low frequency band that can be used to
reduce the cost of deployment. For example, some competing systems
have been proposed in the 60 GHz band, while the presently
disclosed technologies could be deployed in the 3.5 to 5 GHz
frequency band. In another advantageous aspect described in the
present document, a pencil beam can be achieved for data
transmission and used to multiplex transmissions to/from a large
number of users that overlap in other transmission resources, such
as time-frequency dimensions.
[0627] FIG. 84 shows yet another configuration of a fixed access
wireless communication system in which hops are used to reach
users. For example, one cell tower may transmit/receive from
another cell tower, which would then relay the transmissions
between the principle cell tower and the users, thus extending
range of the fixed wireless access system. A backhaul may connect
the transmission tower with an aggregation router. For example, in
one configuration, a 10 Gbps fiber connection may be used to feed
data between a base station at a hub and a fiber hub aggregation
router. In one advantageous aspect, deployment of this technology
can be achieved without having to change any network bandwidth
characteristics for harder to reach areas by using the hub/home
access point (AP) configuration as a launch point.
[0628] As further described in this document, access multiplexing
efficiency can be used by combining one or more of the following
techniques--delay Doppler multiplexing, time-frequency
multiplexing, multiplexing at stream and/or layer level, and
angular multiplexing.
[0629] Time-frequency multiplexing may be achieved using an
approach that divides the time-frequency resource grid for
transmission into multiple subgrids. The subgrids may be of equal
or different sizes. Each subgrid that is used for signal
transmission will be used to carry a two dimensional delay-Doppler
array. In some embodiments, the subgrid structure may occupy the
entire time-frequency two-dimensional plane. Spacing between
subgrids may account for maximum transmission delay and Doppler
spread. This document provides additional details of the various
multiplexing embodiments.
[0630] FIG. 85 shows a pictorial representation of an example of
conversion of a signal between the delay-Doppler domain and the
time-frequency domain. The conversion from delay-Doppler domain to
time-frequency domain may be achieved using a two-dimensional (2D)
OTFS transform. The conversion of signals from time-frequency
domain to the delay-Doppler domain may be achieved using an inverse
2D OTFS transform. In this figure, the OTFS QAM symbols reside on a
grid or lattice of size N.times.M (N and M positive integers). The
OTFS transform translates these QAM symbols to a lattice in the
Time-Frequency plane of size M.times.N (note the swapping of axes a
result of the OTFS transform, as will be explained below). The OTFS
Delay-Doppler lattice and the Time-Frequency multi-carrier lattice
are related through a mathematical reciprocity relation intimately
linked with the symplectic Fourier transform. In this
Time-Frequency domain, one can think of the points along the
frequency axis as the equivalent of an OFDM symbol, made up of M
subcarriers. In the time dimension, we have the equivalent of N
OFDM symbols, where N is a design parameter related to the Doppler
spread of the channel.
[0631] Another observation worth noting in FIG. 85 is the fine
resolution of the Delay-Doppler lattice. In the Delay-Doppler
coordinate system, the delay or multipath resolution is given by
the inverse of the bandwidth and the Doppler resolution is given by
the inverse of the OTFS symbol time or observation time.
[0632] To summarize, in OTFS information symbols are indexed by
points on a lattice or grid in the Delay-Doppler domain. Through
the OTFS Transform each QAM symbol weights a 2D basis function
defined in the Time-Frequency domain. The frequency domain samples
at each time are transformed into time domain waveforms using
filter banks.
[0633] Examples of Time Frequency Multiplexing
[0634] FIG. 86 shows an example of a time frequency grid on which
user data is assigned subgrids of resources. In the depicted
embodiments, subgrids are equal-sized and a 64.times.8 array spans
the entire frequency at 1 msec time granularity per subgrid. In
some embodiments, each subgrid may be used to carry transmission
bursts of 64 to 512 bytes.
[0635] FIG. 87 shows an example of a time frequency grid on which
user data is assigned to two subgrids of resources. As a result of
using different time-frequency resources for the two users, data
capacity can be doubled, while the use of subgrid is still sparse.
The assignments to two users are illustrated via two different
solid circles in each subgrid, representing the transmission
resources for the users.
[0636] FIG. 88 shows an example of a time frequency grid on which
user data is assigned in three subgrids of resources.
[0637] FIG. 89 shows an example of a time frequency grid on which
user data is assigned to eight subgrids of resources.
[0638] FIG. 90 shows an example of a time frequency grid on which
user data is assigned to sixteen subgrids of resources. In this
embodiment, the time frequency grid comprises 512.times.16 array,
with 16 subgrids corresponding to data transmissions
(64.times.8).
[0639] FIG. 91 shows an example of time-frequency resource
assignment to four streams with 32 subsectors of transmission. In
this embodiment, signal transmissions could be organized using 32
subsectors and 4 streams, divided into 4 subbands that are 10 MHz
wide each, and corresponding to 1 msec transmission time interval
(TTI) in a time division duplexing (TDD) transmission scheme.
[0640] Examples of Spatial Multiplexing, Including Steam/Layer and
Angular Multiplexing
[0641] FIG. 92 shows an example of a beam pattern. One of the
advantageous aspects of the disclosed technology is that inter-beam
interference can be managed such that only two neighboring beams
may potentially cause interference to each other. In this regard,
the angular spread of transmission of a base station is controlled
to be small. As a result of such planning, during signal processing
stage to recover signals, the MIMO matrix of the received signal
may be represented using a true tri-diagonal or a block-diagonal
matrix. In other words, the off-diagonal elements may be
represented by zeroes without having to suffer a quality loss due
to rounding assumption. FIG. 92 shows an example of a beam pattern
that can be used in such configurations.
[0642] FIG. 93 shows an example of a dual polarization wide-band
antenna beam pattern. As depicted, the antenna beam pattern could
be controlled along three dimensions--elevation, azimuth and
polarization plane, to achieve denser transmission of data (due to
three dimensional multiplexing). In the depicted embodiment, a
number of antenna elements are used in an array, with one dimension
of the array controlling the azimuth of the transmission beam,
another dimension controlling the elevation and each wideband
antenna achieving dual MIMO for each sector (quadrant of coverage).
Each antenna may be a dual polarization wideband antenna. Each
antenna may be conformal to the hemispherical shape of the dome to
avoid signal distortions and for mechanically snug fitting. The
polarization aspect is pictorially depicted in the bottom part of
the picture.
[0643] FIG. 94 shows the beam pattern footprint of an example of a
24 azimuth.times.5 elevation antenna beam. As can be seen the
coverage is uniform throughout the cell, with the antenna beam
patterns arranged generally to be circular with radii growing
outward from the access point or transmitter.
[0644] FIG. 95 shows an example similar to that depicted in FIG.
93, except that a 4 MIMO antenna configuration is used. As depicted
in the bottom portion of the drawing, four layers of transmission
may be used due to the antenna diversity. As shown, a two
dimensional array of antenna elements (9 azimuth.times.3 elevation)
provides a control over antenna beam pattern ubiquitously in the
space.
[0645] FIG. 96 shows an example of an antenna deployment to achieve
full cell coverage using four quadrant transmissions. Each antenna
may provide coverage to one quadrant of a full 360 degree area,
with collectively, all antennas together may provide uniform
coverage throughout an entire 360 degree area.
[0646] FIG. 97 shows an example of an antenna deployment to achieve
full cell coverage using four quadrant transmissions in a 4 MIMO
antenna configuration system. As depicted, two pairs of four
hemispherical antennas may be used, with each group of four
antennas having a corresponding similar coverage orientation (e.g.,
patterns 1402 and 1404).
[0647] FIG. 98A illustrates an example embodiment of an antenna
system. In the depicted embodiment, a Luneburg antenna
configuration is used. Is shaped to be half-spherical with a
generally planar base and a dome attached to the base. The antenna
includes a hemispherical layered Luneburg lens, with a planar
ultrawideband phased array (PUMA) antenna array arranged
spherically near the spherical surface of the antenna. The planar
portion is the ground plane and may include a heat sink for thermal
regulation. The puma array is shown to have ADI interface and an
interface with a high bandwidth network connection such as a fiber.
The layered Luneburg lens may have dielectric layers of varying
dielectric constants, arranged to provide focal point accuracy of
transmission/reception.
[0648] FIG. 98B illustrates another example embodiments of an
antenna in which dipole antenna are used along the spherical
surface of the hemispherical antenna. A feed network may be
ohmically coupled to the dipole antenna feed to carry signals of
transmission/reception.
[0649] FIG. 98C illustrates an example embodiments of an antenna
which shows a cut-out of the antenna element, showing a heat sink
at the base of the antenna, with the hemispherical dome comprising
layered Luneburg lens above the ground plane, a puma antenna array
coupled to a fiber connection, and enclosed within a radome. The
layered nature of antenna radome (e.g., layered Luneburg lens) is
visible in this cut-out.
[0650] FIG. 98D illustrates an example embodiment of an antenna
with the radome enclosure hiding the electronics and other parts of
the antenna from view and from external environment.
[0651] FIG. 99A shows an example of a cell tower configuration. A
cell tower with existing antenna element deployments can be fitted
with the disclosed antenna elements as depicted in the figure. In
the depicted example, four antenna systems may be fitted to provide
four quadrant coverage, thereby the cell tower providing a complete
360 degree coverage area.
[0652] FIG. 99B shows an example of a cell tower configuration.
Antenna deployment is shown along with the placement of electronics
that implements the base station function functionality (central
rectangular solid box) in a fixed wireless system. In the depicted
embodiment, four antenna systems are used and could be configured
to provide four quadrant coverage.
[0653] FIG. 99C shows yet another cell tower configuration in which
base station electronics is located at a ground level for easy
access by personnel, while antenna elements are positioned towards
or at very top of the antenna tower.
[0654] The disclosed techniques may support up to 1000/b/sec/Hz
peak PHY rate using TDD, a 1 msec TTI, a 4 MIMO antenna
configuration with 32 beams (subsectors), and 40 MHz divided into
four 10 MHz subbands. Data transmissions may be organized into 16
subgrids of a 64.times.8 array, with each subband supporting 64 to
512 bytes of data burst every millisecond per subband, depending on
the constellation used for modulation. Put differently, 8K
logically distinct data payloads could be simultaneously
transmitted (or received), providing a 46 Gbps peak raw throughput
rate per cell (32.times.4.times.40.times.10.times.0.9 Mbps).
[0655] FIG. 100 shows an example of a system deployment in which
OTFS is used for wireless backhaul. A macro cell tower that is
couple to a fiber backhaul may be equipped to carry 380 to 760 Mbps
per hub to provide fixed wireless access to localities. The
transmission distance may be organized in 500-meter range zones.
The hub may be equipped with multiple 1 to N multipoint systems. In
some embodiments, coarse angular separation may be achieved among
different target zones. In some embodiments, multipoint
coordination may be used to further improve transmission
efficiency. In some embodiments, frequency and space division
multiple access may be used.
[0656] FIG. 101 shows another example of a system deployment in
which OTFS is used for wireless backhaul. Compared to the depiction
in FIG. 100, the angular separation in the embodiment of FIG. 101
may be medium. The hub may be equipped with a Luneburg lens pencil
beam antenna configuration to minimize transmission interference.
In some embodiments, time, frequency and/or space division multiple
access may be used to further improve efficiency. Such coverage may
be used for longer-range fixed wireless access. For example, the
distance between the macro tower and areas of coverage may be 5 Km.
In the depicted embodiment, due to the availability of 8 beams, a
total 3 to 6 Gbps bandwidth may be achieved per hub.
[0657] FIG. 102 shows an example deployment of an OTFS based fixed
wireless access system in which UE have MIMO antenna capability.
The range of such a deployment may be extendible to up to 10 KM,
with 32 beams being used for transmission (due to MIMO), thus
providing greater than 20 Gbps bandwidth handling capability per
hub. The angular separation among antenna beam may be finer than
the embodiments depicted in FIG. 100 and FIG. 101, and MU-MIMO
processing may be performed. In some embodiments, azimuthal
interference cancellation may be employed to negate the overlap in
pencil beams. In some embodiments, elevation beamforming may be
used. In some embodiments, up to 4.times.4 MIMO antenna
configuration may be used.
[0658] The use of OTFS modulation in the described deployments thus
offers a way to achieve, or be close to, theoretical capacity at
any MIMO or feedback mode. In some embodiments, a 3D channel
representation may be used during acquisition processing. The OTFS
modulation allows for timely, accurate and low overhead capturing
of mutual coupling between all antenna pairs among all participants
in the network.
6.2 Variable Beamwidth Multiband Antenna
[0659] FIG. 103 shows an example of a lens antenna. As depicted in
the ray drawing on the right (10320), in a traditional lens
antenna, an antenna feed is placed at the focal point of the lens
antenna such that signals transmitted from the antenna feed are
sent into the direction of the associated beam. The graph 10310
shows an example of permittivity of the antenna material as a
function of distance from the center of the sphere to achieve the
focal concentration effect. Two curves are shown--the smooth curve
is the theoretical permittivity, which varies continuously and
smoothly throughout the breadth of the lens, while the step-wise
curve represents a practical implementation in which permittivity
is a step function. Such a practical implementation may be achieved
by layering together several concentric spherical pieces with
variable dielectric properties. The block diagram 10320 shows
convergence of signal beams as they travel through the antenna lens
from air (right hand side) to the focal point, where an antenna
feed is shown to be located.
[0660] The relative dielectric constant at distance r from the
center of the lens to an interior point is given by the equation:
.epsilon..sub.r=2-(r/a).sup.2, where a is the outer radius of the
lens.
[0661] FIG. 104 shows additional examples of antenna designs to
achieve the beamforming. In embodiment 10402, dielectric constant
of the lens material is continuously varied to achieve the desired
focal point of convergence (e.g., similar to the smooth curve in
graph 10310). As depicted, multiple antenna feeds 10400 may be
placed at multiple locations around the spherical lens, thereby
resulting in the antenna being able to transmit multiple signal
beams in different spatial directions.
[0662] In embodiment 10404, discrete material layers may be used,
each layer having a different dielectric constant, to achieve focus
of radiated or received wireless signals in a particular direction.
While only one antenna feed is shown in embodiment 10404, in
general, multiple antenna feeds may be used to enable transmission
of multiple beams.
[0663] FIG. 105 shows an example configuration of an antenna feed
10500 in which multiple antenna feed elements 10502 are used for
transmitting/receiving signals. The antenna feed elements 10502 may
be used in various configurations, as described herein.
[0664] The multiple antenna feed elements 10502 may be driven by a
phased network that provides (or receives) the corresponding
signals to the antenna feed elements 10502. For example, in some
embodiments, an antenna feed 10500 may operate to transmit or
receive wireless signals in multiple frequency bands. Without loss
of generality and only for illustrative purpose, the multi-band
embodiments are described with reference to two frequency bands--a
3.5 GHz frequency band (e.g., between 2.5 and 3.5 GHz or between
3.55 and 3.7 GHz) and a 5.8 GHz frequency band (e.g., frequencies
between 5.1 and 5.9 GHz) for multiple frequency bands. However, it
is understood that the disclosed techniques can be used for
multiple (greater than two) frequency bands at different
operational frequencies.
[0665] The antenna feed 10500 is made up of separate antenna feed
elements 10502, each of which may have its own electrical
connection with a feeder network 10504 that may include a phase
adjustment circuit and/or a diplexer. In one example use case, each
antenna element may be used for transmission/reception of a single
frequency band, with the feeder network 10504 performing the
selectivity of which antenna element to map to which frequency
band. In the depicted example, signals for transmission/reception
within bands 1 to X (where X is an integer) may be fed into the
phase+diplexer network, separated and fed into the antenna feed
elements 10502.
[0666] FIG. 106 shows an example of an antenna feed 10600 in which
multiple antenna elements 10602 are used for transmission using
frequency stacking. For example, frequency stacking may be achieved
by generating a single wideband signal that includes signals in two
or more separate frequency bands. Thus, a frequency stacking
technique may use a same antenna port or antenna element, for
transmitting signals in two different frequency bands. To support
frequency stacking, e.g., allowing at least some antenna feed
elements to transmit or receive signals in multiple frequency
bands, the feeder network 10604 may include a phase adjustment
circuit, one or more diplexers and one or more up/down converters.
The antenna configuration in FIG. 106 may be used to provide
multi-band signals by simultaneously driving signals to (or from)
the antenna elements.
[0667] FIG. 107 shows an example of an antenna feed element
configuration in an antenna feed. In general, the layout and number
of antenna feed elements may depend on frequency band of operation
and on the desired impact on the resulting beamwidths and
beamshapes. Diplexers may be used when antenna feed elements have
wider bandwidth sensitivity than individual antenna port frequency
bands. In some embodiments, in place of the diplexer, a frequency
selective combined phase network may be used.
[0668] In some embodiments, each antenna feed element may be
dedicated to one frequency band, and in general, there may be more
than one antenna feed element for any given band. For example, FIG.
107 depicts that N antenna elements are used for Band_2
communication and M antenna feed elements are used for Band_1
communication. Multiple antenna elements for a given frequency band
may be driven to perform beam-combining as described in the present
document.
[0669] FIG. 108 shows additional examples of possible embodiments
of antenna feeds. As shown in example 10850, an antenna feed may be
operable in two frequency bands--a 3.5 GHz band being coupled with
a phase network (PN) that operates at the 3.5 GHz band, and a
second PN operating at the 5.8 GHz band. Each of these PNs may be
independently connected with corresponding antenna elements via
electrical connections, each connection carrying a band-specific
signal, which is referred to as a narrowband signal (because it
represents less than the entirety of bandwidth handled by the
antenna feed).
[0670] In embodiment 10852, some of the antenna feed elements are
shown to be exclusively coupled with either the 3.5 GHz band PN or
the 5.8 GHz band PN, thus operating in one frequency band only,
while other antenna feed elements are shown to operate in a
wideband configuration in which signals from multiple frequency
bands are frequency stacked to provide (or receive) a wideband
connection through a diplexer. Therefore, in general, an antenna
feed may include antenna feed elements that may include a first
group of dedicated, or narrowband, antenna elements, and a second,
non-overlapping, group of antenna feed elements that operates as a
wideband element that transmits/receives more than one bands of
signals, and possibly all bands in which the antenna feed
operates.
[0671] In embodiment 10854, each antenna feed element is depicted
to be operating as a wideband antenna feed element. Thus, in
embodiment 10854, duplexing for separation/combination of multiple
frequency band signals is performed in the wideband phase network
connected to each of the antenna feed elements.
[0672] The phase network may perform functions such as adjusting
phases of the signals to be transmitted, or fed to each antenna
element, to have the appropriate transmission phase so as to
achieve a target area of coverage. The phase adjustment may take
into account length of the signal path travelled by the signal from
the PN circuit to the antenna element before being radiated from
the antenna element. The phase adjustment may depend on the desired
specific complex linear combination of signals radiated from the
antenna elements (resulting possibly in an additive or subtractive
effect on the magnitude of the signal), as is known in the art.
[0673] FIG. 109 illustrates different possible radial positioning
of antenna elements. In antenna 10902, both the antenna feeds are
positioned at the focal point of a lens antenna. In antenna 10904,
referred to as a "near field" arrangement, the antenna feed is
positioned at an off-focal point, moved off the focal point in the
direction of the signal lobe. In other words, the focal point of
the lens may lie within the body of the antenna feed or behind it.
Explaining in the following for the receive case, in this
arrangement, the electromagnetic signal may impinging upon the
antenna feed before the signal has converged to a focal point
through the lens. In one advantageous aspect, when the antenna feed
includes multiple antenna feed elements, e.g., as shown in FIG.
105, FIG. 106, FIG. 107 or FIG. 108, each antenna feed element may
receive (or transmit) a signal whose characteristics are similar to
a signal received (or transmitted) by the other antenna feed
elements.
[0674] In antenna 10906, the antenna feed is off-focal point in a
direction away from the lens or the direction of the signal beam.
As a result, received signals may first converge at a focal point
and then begin to diverge beyond the focal point prior to impinging
on the surface of the antenna feed. Similar to the antenna 10904,
when multiple antenna feed elements are located on the surface of
the antenna feed, in antenna 10906, the multiple antenna feed
elements may receive/transmit signals similar to each other in
strength.
[0675] FIG. 110 depicts examples of beamforming to achieve a wider
and a narrower beamwidth pattern. A Luneberg lens is used for
illustration, but other similar lenses could also be used (e.g., a
Rotman lens). The variable beamwidth Luneburg lens antenna
illustrates how various antenna feed configurations may be used to
increase or reduce the effective bandwidth of a combined beam
emanating from/received by the antenna feed with multiple antenna
feed elements, as descried with respect to FIGS. 105 to 109. In the
beam pattern 11004, the effective width of the combined beam is
wider than each individual beam to or from an antenna feed. For
example, in a multi-band antenna operation, the beam pattern 11004
may represent one of the bands (e.g., the higher frequency band)
that is serviced by the antenna. In the beam pattern 11006, antenna
elements and signal processing may be arranged to provide an
effective beam width that is narrower than the individual beams
from antenna elements (e.g., the same antenna elements that are
also operating in a different frequency band).
[0676] The embodiment also provides a frequency matched beamwidth.
One desirable configuration may provide the same effective
azimuthal beam width between different frequency bands. The
constructive and/or destructive interference patterns from the
various antenna elements of the same frequency band shape the
effective beam width to match that of the other band(s). In a
variation, the antenna may be operated to provide different beam
widths for different frequency bands. The beamwidth variations may
be achieved by constructive or destructive signal interference,
and/or by using off-focal point antenna placement.
[0677] FIG. 111 shows an example of a variable beamwidth antenna
and a corresponding examples of radiation patterns. One example
configuration may provide a same effective area coverage yet
different beam elevation angles. The multiple antenna feeds may be
tiled in an array along the azimuth and the elevation directions,
as shown in the arrayed arrangement 11106. Antenna feeds creating
beams pointed towards areas that are close to the base station have
multiple elements whose signals are combined to a create wider
beam. Conversely, for further points signals at the elements are
combined to create a narrower beam, such that the actual coverage
is approximately the same as that for the "near" beam described
previously. It will be appreciated that the disclosed embodiments
can thus be used to provide uniform density coverage (configuration
11104) from each antenna feed to a geographic area, irrespective of
the distance of the coverage area from a transmission station at
which the antenna is installed for operation. One example
advantageous property is that this configuration overcomes
operational problems associated with the coverage footprint
depicted in configuration 11102, in which the zone or area of the
covered area increases at distances farther away from the antenna
location. For example, at the transmission station at which such an
antenna is installed, network backhaul resources can be uniformly
allocated to each antenna element due to its uniform density
coverage, instead of having to allocate non-uniform transmission
resources based on the size of the covered area.
[0678] In some embodiments, an antenna system includes an antenna
lens such as a Luneburg lens or a Rotman lens and one or more
antenna feeds placed at on or off focal point of the antenna lens
(e.g., as depicted in FIG. 109). The position of the antenna feed
may thus be far-field (behind focal point) or near-field (in front
of the focal point, in the direction of beam). Each of the one or
more antenna feeds comprises one or more antenna feed elements that
are electrically independently operable. The antenna system also
includes an antenna feed network, or a phase network (PN)
electrically coupled with the one or more antenna feed elements via
signal paths or connections. In some embodiments, each of the
antenna feeds is designated to operate in one or more frequency
bands and wherein position and/or size of the one or more antenna
feed elements for each antenna feed depends on the one or more
frequency bands of operation. In some embodiments, at least one
antenna feed is capable of simultaneous operation in at least two
frequency bands and wherein the at least one antenna feed includes
multiple antenna elements that are grouped to operate in different
ones of the at least two frequency bands.
[0679] In some embodiments, at least one antenna feed is capable of
simultaneous operation in at least two frequency bands and wherein
at least one antenna feed includes an antenna feed element that is
coupled to the antenna feed network using a frequency stacked
configuration in which the antenna feed element simultaneously
receives or transmits signals in two different frequency bands and
wherein the antenna feed network includes a diplexer.
[0680] In some embodiments, the antenna system includes a data feed
that is positioned conformal to the antenna lens. For example, as
depicted in FIG. 111, an array of antennas may be placed around the
spherical lens surface.
6.3 SWAP Optimized Devices for OTFS Communication
[0681] Techniques using orthogonal time frequency space (OTFS)
modulation enable precoding of a transmitted signal on a
symbol-by-symbol basis. The rapid adjustment of precoded OTFS
modulated signals may improve reception by moving receivers or
receivers in environments with moving reflectors or interferers.
The rapid adjustment of precoded OTFS modulated signals may support
multiple simultaneous users.
[0682] A portion of the computational complexity used by a
communication link using precoded OTFS modulated signals resides in
the transmitter. In some example embodiments, the receiver may be
simplified to a matched filter receiver. Because the receivers of
precoded OTFS modulated signals may not have much complexity, they
may be small in size, use little power, and may be inexpensive. The
receivers including antennas may also take any shape. Some
receivers may be end nodes where the data received is consumed at
the end node. A remotely controlled light switch that includes the
receiver is an example of a device where the data is consumed by
the device to control the light switch. Some receivers may
re-transmit to another device the data received. For example, a
receiver may receive a OTFS modulated signal to determine data and
re-transmit the data to another device.
[0683] FIG. 112 depicts an example of two communications networks,
in accordance with some example embodiments. FIG. 112 includes
cellular base station 11210, cellular phone 11220, OTFS base
station 11230, and OTFS surface 11240.
[0684] Cellular base station 11210 may include any type of cellular
base station. For example, cellular base station 11210 may be a
base station fixed in location that provides communication via a
1G, 2G, 3G, 4G, LTE, 5G or any other cellular system or standard.
In some example embodiments, cellular base station 11210 is located
on an aircraft and as such may be mobile rather than stationary.
Cellular base station 11210 is in communication with phone 11220.
Phone 11220 may receive digital data related to voice and/or
Internet Protocol (IP) data representative of voice. Phone 11220
may receive IP data from base station 11210 related to web
browsing, file transfers, applications, or any other digital data
consumer on phone 11220.
[0685] OTFS base station 11230 may be in communication with OTFS
surface 11240. OTFS base station 11230 may be fixed in location or
may be mobile. OTFS base station 11230 may communicate with OTFS
surface 11240. By using OTFS, OTFS base station 11230 can adjust
modulation and transmission parameters on a symbol by symbol basis
thereby creating a more reliable and customized data rate to the
OTFS surface 11240. Some OTFS surfaces may require low data rates
while others may require higher data rates. The shape, size, and/or
power parameters of the OTFS surface can influence the customized
data rate. For example, smaller OTFS surfaces and/or lower power
OTFS surfaces may be customized for lower data rates than larger
and./or higher power surfaces. Such customization allows the design
of an OTFS surface to meet the requirements of the end application
without being constrained by the material, shape, and size of the
surface. For example, a cuff link used as an OTFS surface may
maintain its cuff link shape when being used as an OTFS surface and
the data rate to the cuff link may be customized according the
size, shape, and available power at the cuff link.
[0686] OTFS surface 11240 may include a receiving surface such as
the surface of an object that is used as an antenna to receive
signals from OTFS base station 11230. OTFS surface 11240 may also
serve a non-electrical function such as holding cuffs of a shirt
together, or as a case to protect a cell/smart phone, or case to
protect a laptop/netbook or other portable device. For example,
OTFS surface 11240 may include an external case within which a
cellular phone, tablet, or portable computer is held. The external
case may include an antenna or array of antennas such as a patch
array antenna, or other antenna. The external case may include a
receiver, transmitter, or transceiver that uses the antenna or
array of antennas for reception and/or transmission. For example, a
thin form fitting case may be placed on a smartphone that includes
the forgoing antenna embedded in the case material. Also embedded
in the case may be a receiver, transmitter, or transceiver to
communicate with OTFS base station 11230.
[0687] In some example embodiments OTFS surface 11240 may receive
data from OTFS base station 11230 that is consumed at OTFS surface
11240. The OTFS surface may have another function, a non-electrical
function different from being an antenna or receiving surface. For
example, OTFS surface 11240 may be formed into a cuff link, button,
placed in jewelry, on eyeglasses, door locks, other locks, or other
devices where a change to the device may be performed remotely. As
illustrative examples, a cuff link used to hold the cuffs of a
shirt sleeve together may also receive data to affect a color of
the cuff link, or to affect a latching mechanism to release latch
the cuff link. The foregoing changes to the cuff link may be based
on a signal received from OTFS base station 11230. OTFS surface
11240 formed into a button that may be controlled via OTFS base
station 11230 to change the appearance of the button, or to
disengage the button to cause an unbuttoning. Eyeglasses may be
controlled via an OTFS signal received to cause tinting of the
glasses to change. Locks may be controlled via an OTFS signal
received to cause the lock to lock or unlock. May other devices may
be controlled or caused to change via an OTFS signal received at
the device from base station 11230.
[0688] Many other applications such as devices in the Internet of
Things (IoT) including refrigerators, washers, dishwashers, HVAC
systems, irrigation systems, and any other home, commercial, or
industrial devices may include OTFS surface 11240. The foregoing
applications may be controlled via messages sent from the OTFS base
station to each device.
[0689] In some example embodiments, phone 11220 may send a signal
to cellular base station that is forwarded or otherwise causes OTFS
base station 11230 to send a signal message to the cuff link,
button, jewelry, or other OTFS surface. For example, an application
running on phone 11220 may pass a message or command through
cellular base station 11210 to OTFS base station 11230. One or more
intervening networks such as a core network may lie between
cellular base station 11210 and OTFS base station 11230. The
message or command may be passed from OTFS base station 11230 to
OTFS surface 11240 and may cause a change the a feature or
parameter of the device as described above. OTFS surfaces where the
message, command, or other data is used at the device and is not
forwarded to another device may be referred to as OTFS end
points.
[0690] In some example embodiments, OTFS surface 11240 includes a
wired or wireless interface 11250 between phone 11220 and OTFS
surface 11240. For example, OTFS surface 11240 may communicate with
phone 11220 via a short range optical or radio frequency interface
such as a Bluetooth interface. Data received at OTFS surface 11240
from base station 11230 may be passed via interface 11250 to phone
11220. For example, the data received via interface 11250 over the
OTFS communication link may augment the data throughput capacity to
phone 11220. In some example embodiments, when phone 11220 has no
connection to base station 11210, OTFS base station 11230 may
replace the cellular service and provide data and voice
connectivity between phone 11220 and another phone or a core
network.
[0691] FIG. 113 depicts an example of an OTFS network, in
accordance with some example embodiments. In the example of FIG.
113, data services and backbone cellular services are provided to
structure 11310 via the communication between OTFS base station
11330 and OTFS modem 11320. OTFS modem 11320 may provide data to
wired and wireless networking device 11330 and/or to femto-cell
11340. In some example embodiments, structure 11310 may be a house,
office building, or other fixed structure. In other example
embodiments, structure 11310 may be mobile such as an automobile,
bus, truck, train, airplane, or other vehicle.
[0692] OTFS base station 11330 may provide wireless service to
structure 11310. OTFS base station 11330 may connect to a core
network that may provide digital data such as IP data and/or voice
service to structure 11310 via OTFS modem 11320. In some example
embodiments, OTFS baste station 11330 may provide backbone service
to modem 11320 to support a cellular femto-cell 11340 in or near
structure 11310.
[0693] OTFS modem 11320 may provide data service to wired and
wireless networking device 11330. Wired and wireless networking
device 11330 may provide data service via WiFi (e.g., IEEE 802.11
family of standards) or other wireless standard, via Ethernet
(e.g., IEEE 802.3 family of standards) or other wired networking
standard to computer 11360 and/or phone 11350. Phone 11350 may be
provided cellular service via femto-cell 11340 which may include
data service for Internet data or other data.
[0694] FIG. 114 an example of an OTFS network and a wired network,
in accordance with some example embodiments. FIG. 114 is similar to
FIG. 113 except that FIG. 114 includes wireline service via cable
11410 and wireline modem 11420 to provide IP and other data to
structure 11410. In the example of FIG. 114, the wireline data may
provide a baseline data service to structure 11410 including data
to wired and wireless networking device 11430. OTFS base station
11430 may provide backbone cellular data service for femto-cell
11440. When service is not available via cable 11410 and wireline
modem 11420, OTFS modem 11420 may instead provide service to wired
and wireless networking device 11430 and the supported devices such
as computer 11460 and/or phone 11450. Service via cable 11410 and
wireline modem 11420 may not be available when a wireline system
fails or wireline modem 11420 fails so that no data is available
(or a reduced throughput) via cable 11410.
[0695] FIG. 115 depicts examples of cases and enclosures that are
OTFS surfaces, in accordance with some example embodiments. FIG.
115 depicts examples of cases 11510 and 11520 for smartphones that
include OTFS surfaces. At 11530, 11540, and 11550 are enclosures
that include OTFS surfaces. The enclosures may protect electronic
or electrical equipment form the environment as well as being OTFS
surfaces. The enclosures may house electronics or electrical
equipment related to, or unrelated to, networking or data
communications.
[0696] It will be appreciated that the disclosed techniques can be
used to implement embodiments in which a surface of an object,
which is intended to perform a non-digital communication function
such as heat sink, or screen protection, or other examples given in
the present document, can also be adapted for OTFS signal
reception. The surface may also be adapted to transmit OTFS
signals. Using the pre-coding techniques described in Section 4,
hundreds and hundreds of receiving devices with their antenna
surfaces may be provided with network connectivity using digital
communication techniques such as massive MIMO and pre-coding.
[0697] With regard to the embodiments described above, the features
may be included in any combination. The wireless receiver may
include a transmitter to transmit the determined digital data
according to a short-range wireless standard. The wireless receiver
may include a cellular femto-cell transmitter to transmit the
determined digital data according to a cellular radio standard. The
cellular radio standard may include one or more of a 3G standard, a
4G standard, a Long Term Evolution standard, or a 5G standard. The
digital amplitude modulation constellation may be mapped to a
delay-Doppler domain by transforming the digital amplitude
modulation signal into a 2D transformed orthogonal time frequency
space signal using a 2D Fourier transform from a 2D time-frequency
domain to a 2D delay-Doppler domain. The digital amplitude
modulation constellation may be a quadrature amplitude modulation
(QAM). The surface may be a cellular phone case and the wireless
receiver apparatus may be embedded in the cellular phone case. The
surface may be configured as a clothing button. The surface may be
an eyeglass frame. The surface may be a lock.
6.4 Light Bulbs with Integrated Antennas
[0698] This section discloses implementations that include light
bulbs for illumination of an area that include wireless antennas
for wireless communications. For example, a street light or other
exterior light may provide illumination of a road or sidewalk or
other area. In the disclosed subject matter, the bulb portion in
the street light includes one or more electronically steerable
antennas for wireless communications. Each electronically steerable
antenna may include a plurality of other antennas where real-time
adjustment of phasing and amplitude of electronic feeds to the
other antennas antenna causes steering of one or more beams
associated with each electronically steerable antenna. The one or
more electronically steerable antennas may be used in a multiple
input multiple output (MIMO) communication scheme, including, for
example, in massive MIMO configurations with 64 or 128 or higher
transmit antennas. The one or more steerable antennas may be used
to transmit signals, or a combination of signals including
orthogonal time frequency space (OTFS) modulation, WiFi (any of the
IEEE 802.11 family of standards), or cellular standards including
4G, 5G or other cellular standard. Use of OTFS provides some
advantages which are described below.
[0699] Techniques using orthogonal time frequency space (OTFS)
modulation enable precoding of a transmitted signal on a
symbol-by-symbol basis thereby creating a more reliable and
customized data rate. Some OTFS devices may use low data rates and
others may use high data rates. The rapid adjustment of precoded
OTFS modulated signals may improve reception by moving receivers or
receivers in environments with moving reflectors or interferers.
The rapid adjustment of precoded OTFS modulated signals may support
multiple simultaneous users. A portion of the computational
complexity used by a communication link using precoded OTFS
modulated signals resides in the transmitter. In some example
embodiments, the receiver may be simplified to a matched filter
receiver. Because the receivers of precoded OTFS modulated signals
may not have much complexity, they may be small in size, may be
formed into any shape, may use little power, and may be
inexpensive. The shape, size, and power of an OTFS device may
influence the data rate provided to the device with higher power
and/or larger antenna size offering higher data rates. Some
receivers may be end nodes where the data received is consumed at
the end node. Some receivers may re-transmit to another device the
data received. For example, a receiver may receive a OTFS modulated
signal to determine data and re-transmit the data to another
device.
[0700] FIG. 116 depicts an example of a wireless system 11600
including a light bulb with integrated antennas, in accordance with
some example embodiments. Wireless system 11600 includes ground
station 11650 in communication with light pole 11605 and/or 11635
and wireless device 11620 in communication with light pole 11605
and/or 11635.
[0701] Light poles 11605 and 11635 include light bulbs 11610 and
11630, respectively. Light bulbs 11610 and 11630 may provide
illumination underneath the light poles 11605 and 11635. For
example, the light bulbs may illuminate a street or sidewalk or
other area underneath the light poles. The light bulbs may include
light emitting diode (LED) light sources or other light sources.
The light sources may be arranged in a radially symmetrical manner
in the light bulb--e.g., on circumference of radome of an antenna,
as described in the present document. The number of light sources
and their placement may be determined based on the light
illumination power of each light source, the total illumination
requirement and a desired or target beam of light illumination.
[0702] Light bulbs 11610 and 11630 include antennas for wireless
communications. The embodiments may also be described as antennas
that include illumination function. In one advantageous aspect, the
hemispherical antenna appearance may provide the aesthetic look of
a conventional street pole light fixture, while at the same time
provide wireless connectivity. For example, an antenna in light
bulb 11610 may communicate with wireless device 11620. The antenna
in 11610 may also communicate wirelessly with ground station 11650.
For example, ground station 11650 may be an internet service
provider that may provide data service to light bulb 11610 via
connection 11645. Light bulb 11610 may perform as an access point
to provide data service to wireless device 11620 via connection
11615. Data may be passed from ground station 11650 thru light bulb
11610 to wireless device 11620 via connection 11615. Data may be
passed from wireless device 11620 thru light bulb 11610 to ground
station 11650 via connection 11615.
[0703] Wireless device 11620 may be within range of the antennas at
one or more light poles. For example, wireless device may be within
range of an antenna in light bulb 11610 at light pole 11605 via
connection 11615 and may be within range of light bulb 11630 at
light pole 11635 via connection 11625. When the signals from both
light poles are sufficiently high, wireless device 11620 may select
which light pole to communicate with, or wireless device may
commanded to use one of the light poles, or no selection may be
made. Wireless device 11620 may include a phone, smartphone,
laptop, netbook, or any other wireless device. The data passed
between wireless device 11620 and one or more light poles may
operate using OTFS or other wireless communication scheme. Wireless
device 11620 may be mobile whereas wireless device 120 moves,
communication with the wireless device may be handed-off to
different light poles according to the movement.
[0704] Ground station 11650 may be a central office, hub, or other
station providing data communication service to remote access
points such as light poles and/or wireless devices. Ground station
11650 may provide wired or wireless service to remote access points
such as light poles 11605 and 11635. For example, ground station
11650 may provide wired or fiber optic communication to light pole
11635. In turn, light pole 11635 may provide wireless access to one
or more wireless devices such as wireless device 11620. Ground
station 11650 may provide wireless communications to light pole
11605. In turn, light pole 11605 may provide wireless access to one
or more wireless devices such as wireless device 11620. In some
example embodiments, a light pole may perform as a relay from
ground station 11650 to another light pole. For example, ground
station 11650 may wirelessly provide data service to light pole
11605 via connection 11645, and light pole 11605 may act as a relay
to light pole 11635 via connection 11640, and light pole 11635 may
provide data service to wireless device 11620 via connection 11625.
In another example, ground station 11650 may provide data service
to light pole 11635 via wired connection 11655, and light pole
11635 may act as a relay to light pole 11605 via connection 11640,
and light pole 11605 may provide data service to wireless device
11620 via connection 11615.
[0705] FIG. 117 depicts an example of a light pole 11700 and an
exploded view of the top of the light pole including a light bulb,
in accordance with some example embodiments. The light bulb 11705
includes light sources 11710 which may be LEDs or other light
sources. Five light sources are shown in FIG. 117 but any other
number of light sources may be used. In some example embodiments,
light bulb 11705 also includes a housing for the light bulb. For
example, light bulb 11705 may be mounted or housed in a housing
that may be mounted to a light pole. In some example embodiments,
light bulb 11705 is a direct replacement for an existing street
light such as a sodium street lamp or other street light. As a
direct replacement, light bulb 11705 may provide the same or better
lighting than the street lamp it replaces in addition to providing
wireless services not provided by the original street lamp. Light
bulb 11705 includes one or more antennas such as an antenna at
11720. The one or more antennas may be conformal to a curved
surface. One or more of the antennas may include a Luneburg lens to
focus and direct the electromagnetic waves to/from the antennas in
light bulb 11705. Light bulb 11705 may also include a radome
11730.
[0706] FIG. 118 depicts another example of a light pole 11800 with
a light bulb that includes antennas for wireless communications, in
accordance with some example embodiments. In the example of FIG.
118, two light bulbs with integrated antennas 11810 are shown
attached to pole 11840. The light bulbs and antennas may be similar
to those described with respect to FIG. 117. Light bulbs with
integrated antennas 11810 may be connected through pole 11840 to
base electronics 11840. Base electronics 11850 may include power
supply circuits, networking circuits, power amplifiers,
modulation/demodulation, and other signal processing and/or
networking circuits. In addition to being placed on light poles,
the light bulbs and integrated antennas may be mounted to a
building 11870.
[0707] FIG. 119 depicts an example of a light pole 11900 including
a light bulb, an antenna, and signal processing electronics, in
accordance with some example embodiments. In the example of FIG.
119, some or all of the base electronics such as base electronics
11850 in FIG. 118 may be mounted on the light pole at an above
ground location. In the example of FIG. 119, the base electronics
11910 is mounted near the top of the light pole near where light
bulb 11905 is located.
[0708] FIG. 120 depicts an example of a mast mounted antenna 12010
and an example of a pole mounted antenna 12050, in accordance with
some example embodiments.
[0709] Mast mounted antenna 510 and/or pole mounted antenna 12050
may include four or another number of antennas. In the examples
shown at 12010 and 12050, each antenna 12015 may provide coverage
for a quadrant of hemispherical space. Other numbers of antennas
with different corresponding coverages may also be used. In the
example at 12010, antennas 12015 may provide 4.times.4 MIMO, each
antenna 12015 may include two internal antennas. Other numbers of
internal antennas and other MIMO diversity values may be
provided.
[0710] FIG. 121 depicts an example of a tower mounted antenna 12110
and another example of a pole mounted antenna 12120, in accordance
with some example embodiments.
[0711] The example tower mounted antenna shown at 12110 includes
two antennas 12115. Each antenna 12115 may provide coverage for
half of hemispherical space. In the example at 12110, antennas
12115 may provide 2.times.2 MIMO, each antenna 12115 may include
two internal antennas. Other numbers of internal antennas and other
MIMO diversity values may be provided.
[0712] The example light pole mounted antenna shown at 12120
includes four antennas 12125. Each antenna 12125 may provide
coverage for quadrant of hemispherical space. In the example at
12120, antennas 12125 may provide 2.times.2 MIMO, each antenna
12125 may include two internal antennas. Other numbers of internal
antennas and other MIMO diversity values may be provided.
[0713] It will be appreciated that the present document discloses
an apparatus that combines wireless transmissions/reception antenna
functionality with light illumination functionality. Due to the
antenna design, and placement of light on the outer perimeter of
the antenna (e.g., at the ground plane of the hemispherical
antenna), the operation of light sources and antenna can occur
simultaneously, and without interfering with each other.
[0714] FIG. 122 depicts an example of a light pole, in accordance
with some example embodiments. The example of FIG. 122 shows, at
12220, one or more lights and one or more antennas as described
above. At 12210 a housing for the light and antenna device is
shown. At 12230 is a pole supporting 12210 and 12220. The height of
the pole is shown to be approximately 5 feet but the pole may be
any other height such as the height of a street light pole. Pole
12230 is held in place by the base 12240. Base 12240 may be a plate
of material such as metal or the base may be concrete such as a
light pole installed in the ground. The "half coat hanger" shaped
structures on top of the light bulb area may be used as heat sinks
to dissipate the heat generated during the operation of light
and/or communication aspects. In some embodiments, pole 12230 may
instead be attached to the side of a building or other object and
may provide dual function of illumination and wireless
connectivity.
[0715] With regard to the embodiments described above, the
following features may be included in any combination. The light
bulb may be coupled to a light pole. The light pole may be a street
light pole. The light bulb may illuminate an area of ground
including one or more of a street, sidewalk, walkway, dirt area, or
other outside area. The steerable directional antenna may include a
luneberg lens. The steerable directional antenna may support a MIMO
communications scheme. The light bulb may further include a
cellular transceiver, a WiFi transceiver, or other wireless
networking transceiver. The cellular transceiver may support one or
more of a 3G standard, a 4G standard, a Long Term Evolution
standard, or a 5G standard. A digital amplitude modulation
constellation may be mapped to a delay-Doppler domain by
transforming the digital amplitude modulation signal into a 2D
transformed orthogonal time frequency space signal using a 2D
Fourier transform from a 2D time-frequency domain to a 2D
delay-Doppler domain.
[0716] Some embodiments and techniques may be described using the
following clause-based description.
[0717] 1. A light bulb apparatus, comprising:
[0718] one or more light sources; and a steerable directional
antenna coupled to the one or more light sources, wherein the
steerable directional antenna is further coupled to a transmitter,
wherein the transmitter maps digital data to a digital amplitude
modulation constellation in a time-frequency space, and wherein the
digital amplitude modulation constellation is mapped to a
delay-Doppler domain and transmitted to the steerable directional
antenna according to an orthogonal time frequency space (OTFS)
modulation signal scheme.
[0719] 2. The apparatus of clause 1, wherein the light bulb is
coupled to a light pole.
[0720] 3. The apparatus of clause 2, wherein the light pole is a
street light pole.
[0721] 4. The apparatus of clause 1, wherein the light bulb
illuminates an area of ground including one or more of a street,
sidewalk, walkway, dirt area, or other outside area.
[0722] 5. The apparatus of clause 1, wherein the steerable
directional antenna includes a Luneburg lens.
[0723] 6. The apparatus of clause 5, wherein the steerable
directional antenna supports a MIMO communications scheme.
[0724] 7. The apparatus of clause 1, wherein the light bulb
apparatus further comprises:
[0725] a cellular transceiver, a WiFi transceiver, or other
wireless networking transceiver.
[0726] 8. The apparatus of clause 7, wherein the cellular
transceiver supports one or more of a 3G standard, a 4G standard, a
Long Term Evolution standard, or a 5G standard.
[0727] 9. The apparatus of clause 1, wherein the digital amplitude
modulation constellation is mapped to a delay-Doppler domain by
transforming the digital amplitude modulation signal into a 2D
transformed orthogonal time frequency space signal using a 2D
Fourier transform from a 2D time-frequency domain to a 2D
delay-Doppler domain.
[0728] 10. A method of illumination and wireless networking, the
method comprising:
[0729] illuminating, by one or more light sources, an area of
street, sidewalk, or ground; and
[0730] wirelessly communicating to a user node via a steerable
directional antenna coupled to the one or more light sources,
wherein the steerable directional antenna is further coupled to a
transmitter, wherein the transmitter maps digital data to a digital
amplitude modulation constellation in a time-frequency space, and
wherein the digital amplitude modulation constellation is mapped to
a delay-Doppler domain and transmitted to the steerable directional
antenna according to an orthogonal time frequency space (OTFS)
modulation signal scheme.
[0731] 11. The method of clause 10, wherein the light bulb is
coupled to a light pole.
[0732] 12. The method of clause 11, wherein the light pole is a
street light pole.
[0733] 13. The method of clause 10, wherein the steerable
directional antenna includes a luneberg lens.
[0734] 14. The method of clause 10, wherein the steerable
directional antenna supports a MIMO communications scheme.
Section 7: Exemplary Methods for Implementation Aspects for
OTFS
[0735] FIG. 123 is a flowchart showing operations performed in an
example method 12300 for wireless communication. The method 12300
includes, at step 12310, allocating resources for wireless
transmissions, wherein the resources correspond to resource
elements in one or more two-dimensional transmission frames,
wherein each transmission frame comprises a first number of units
along a delay dimension and a second number of units along a
Doppler dimension, and wherein an aspect ratio of the transmission
frame is variable over a time period. The method 12300 includes, at
step 12320, generating a waveform based on the allocated
resources.
[0736] FIG. 124 is a flowchart showing operations performed in an
example method 12400 for wireless communication. The method 12400
includes, at step 12410, receiving, at a user device, information
associated with resources allocated for wireless transmissions,
wherein the resources correspond to resource elements in one or
more two-dimensional transmission frames, wherein each transmission
frame comprises a first number of units along a delay dimension and
a second number of units along a Doppler dimension, and wherein an
aspect ratio of the transmission frame is variable over a time
period.
[0737] The method 12400 includes, at step 12420, transmitting or
receiving a waveform using the information pertaining to the user
device.
[0738] FIG. 125 is a flowchart showing operations performed in an
example method 12500 for wireless communication. The method 12500
includes, at step 12510, precoding by applying a Doppler dimension
transform to the data bits, thereby producing precoded data.
[0739] The method 12500 includes, at step 12520, mapping the
precoded data to transmission resources in one or more Doppler
dimensions, along a delay dimension.
[0740] The method 12500 includes, at step 12530, generating
transformed data by transforming the precoded data using an
orthogonal time frequency space transform.
[0741] The method 12500 includes, at step 12540, converting the
transformed data into a time domain waveform corresponding to the
signal.
[0742] FIG. 126 is a flowchart showing operations performed in an
example method 12600 for wireless communication. The method 12600
includes, at step 12610, converting a received time domain waveform
into an orthogonal time frequency space (OTFS) signal by performing
an inverse OTFS transform. The method 12600 includes, at step
12620, extracting, from the OTFS signal, modulated symbols along
one or more Doppler dimensions. The method 12600 includes, at step
12630, applying an inverse precoding transform to the extracted
modulated symbols. The method 12600 includes, at step 12640,
recovering data bits from an output of the inverse precoding
transform.
[0743] In methods 12300, 12400, 12500 and 12600, the aspect ratio
of the transmission frame (e.g., the ratio of number of delay units
and number of dimension units) may be changed over a period of
time. This change may be performed to accommodate user data packet
size changes. For example, the aspect ratio may be changed such
that one user device packet maps to one PRB in the delay-Doppler
grid. Various methods may be used for signaling the change from a
transmitting device (or a device that controls resource scheduling)
to a receiving device. The signaling may be performed sufficiently
in advance (e.g., 1 millisecond, or one transmit time interval TTI)
so that the receiving device may adapt its PHY and MAC for the
change in the aspect ratio.
[0744] In some embodiments, the methods 12300, 12400, 12500 and
12600 may operate using transmission frames that are made up of
physical resource blocks that comprise a fixed number of resource
elements along the Doppler domain. Each assigned Doppler domain
resource may include one or more PRBs, as may be selected based on
user data packet size.
[0745] Some embodiments and techniques related to methods 12300,
12400, 12500 and 12600 may be described using the following
clause-based description.
[0746] 1. A method of allocating transmission resources,
comprising:
[0747] allocating resources for wireless transmissions, wherein the
resources correspond to resource elements in one or more
two-dimensional transmission frames, wherein each transmission
frame comprises a first number of units along a delay dimension and
a second number of units along a Doppler dimension, and wherein an
aspect ratio of the transmission frame is variable over a time
period; and generating a waveform based on the allocated
resources.
[0748] 2. The method of clause 1, further including: changing an
aspect ratio of the transmission frame in response to a size of
user data packets.
[0749] 3. The method of clauses 1 or 2, wherein the transmission
resources correspond to uplink transmissions by multiple user
devices, and wherein the method further comprises: signaling the
aspect ratio or a change in the aspect ratio using a scheme from
one or more of: (a) downlink control channel signaling, (b) upper
layer signaling, (c) implicit indication, or (d) signal
detection.
[0750] 4. The method of clauses 1 or 2, wherein the transmission
resources correspond to downlink transmissions to one or more user
devices, and wherein the method further comprises:
[0751] signaling the aspect ratio or a change in the aspect ratio
using a scheme from one or more of: (a) common downlink control
channel signaling, (b) upper layer signaling, (c) implicit
indication, or (d) signal detection.
[0752] 5. The method of any of clauses 1 to 4, further comprising:
signaling one or more of subcarrier spacing, a number of
sub-carriers in the transmission frames, a number of symbols in the
transmission frames, symbol duration and cyclic prefix
duration.
[0753] 6. The method of any of clauses 1 to 5, wherein the
transmission frames comprise physical resource blocks that comprise
a fixed number of resource elements along the delay domain in one
Doppler dimension.
[0754] 7. The method of clause 6, wherein each Doppler domain value
comprises one or more physical resource blocks.
[0755] 8. The method of clause 2, wherein the changing the aspect
ratio includes selecting a number of delay dimension units to be
equal to number of resource elements in one physical resource block
or an integer number of physical resource blocks, and wherein a
number of Doppler dimension units is adjusted such that the number
of resource elements in a rectangular matrix is a constant.
[0756] 9. A method of wireless communication, comprising:
[0757] receiving, at a user device, information associated with
resources allocated for wireless transmissions, wherein the
resources correspond to resource elements in one or more
two-dimensional transmission frames, wherein each transmission
frame comprises a first number of units along a delay dimension and
a second number of units along a Doppler dimension, and wherein an
aspect ratio of the transmission frame is variable over a time
period; and transmitting or receiving a waveform using the
information pertaining to the user device.
[0758] 10. The method of clause 9, wherein the transmitting the
waveform includes transmitting the waveform that is a mathematical
equivalent of a target waveform generated by assigning data symbols
to resource elements and converting a resulting signal into
time-domain by an operation comprising a first step is a
2-dimensional Fourier transform to convert the resulting signal to
the time-frequency domains, and a second step of converting an
output signal of the first step to the time-domain by performing an
inverse Fourier transform, and prepending a cyclic prefix to every
orthogonal frequency division multiplexing symbol.
[0759] 11. The method of clause 9, wherein the transmitting the
waveform includes transmitting the waveform that is a mathematical
equivalent of a target waveform generated by assigning data symbols
to resource elements and converting a resulting signal into
time-domain by an operation comprising a single step of applying a
Fourier transform to convert from Doppler to time dimension.
[0760] 12. A method of wireless communication, comprising:
generating, from data bits, a signal for transmission wherein the
signal corresponds to an output of operations of: precoding by
applying a Doppler dimension transform to the data bits, thereby
producing precoded data; mapping the precoded data to transmission
resources in one or more Doppler dimensions, along a delay
dimension; generating transformed data by transforming the precoded
data using an orthogonal time frequency space transform; and
converting the transformed data into a time-domain waveform
corresponding to the signal.
[0761] 13. The method of clause 12, wherein the Doppler dimension
transform has a size that is a function of size of data bits.
[0762] 14. A method of wireless communication, comprising:
[0763] generating, from a received signal, data bits wherein the
signal corresponds to an output of transmitter-side operations of:
precoding by applying a Doppler dimension transform to the data
bits, thereby producing precoded data; mapping the precoded data to
transmission resources in one or more Doppler dimensions, along a
delay dimension; generating transformed data by transforming the
precoded data using an orthogonal time frequency space transform;
and converting the transformed data into a time-domain
waveform.
[0764] 15. The method of clause 14, wherein the Doppler dimension
transform has a size that is a function of size of data bits.
[0765] 16. A method of wireless communication, comprising:
converting a received time-domain waveform into an orthogonal time
frequency space (OTFS) signal by performing an inverse OTFS
transform; extracting, from the OTFS signal, modulated symbols
along one or more Doppler dimensions; applying an inverse precoding
transform to the extracted modulated symbols; and recovering data
bits from an output of the inverse precoding transform.
[0766] 17. The method of any of clauses 12 to 16, wherein the
precoding transform is a discrete Fourier transform (DFT).
[0767] 18. The method of clause 16, wherein performing the inverse
OTFS transform comprises: converting the received time-domain
waveform to a waveform in a frequency-time plane based on a
conventional OFDM demodulation process; and converting the waveform
in the frequency-time plane to the OTFS signal in a delay-Doppler
plane using an inverse symplectic transform.
[0768] 19. The method of clause 16, wherein performing the inverse
OTFS transform comprises: converting the received time-domain
waveform to the OTFS signal in a delay-Doppler plane based on an
Fourier transform in a Doppler domain.
[0769] FIG. 127 is a flowchart showing operations performed in an
example method 12700 for wireless communication using an orthogonal
time frequency space (OTFS) signal comprising one or more OTFS
frames in a two-dimensional delay-Doppler domain grid. The method
12700 includes, at step 12710, generating a signal by concatenating
orthogonal time frequency space (OTFS) symbols in a CP-less
(cyclic-prefix-less) manner, wherein in each OTFS frame in a
two-dimensional delay-Doppler domain grid, for at least some
Doppler domain values, a split allocation scheme is used for
assigning transmission resources along delay dimension, wherein the
split allocation scheme includes allocating a first portion to user
data symbols and a second portion to non-user data symbols.
[0770] In some embodiments, each Doppler domain value includes the
split allocation. In other embodiments, each Doppler domain value
comprises a same size of the second portion.
[0771] The method 12700 includes, at step 12720, transmitting the
signal over a wireless channel.
[0772] FIG. 128 is a flowchart showing operations performed in an
example method 12800 for wireless communication using an orthogonal
time frequency space (OTFS) signal comprising one or more OTFS
frames in a two-dimensional delay-Doppler domain grid. The method
12800 includes, at step 12810, partitioning resource elements of an
OTFS frame into a first set and a second set that include resource
elements along a delay dimension of the two-dimensional
delay-Doppler domain grid. The method 12800 includes, at step
12820, using the first set of resource elements for non-user data
symbols. The method 12800 includes, at step 12830, using the second
set of resource elements to user data symbols, wherein the second
set of resource elements comprises lower-numbered delay domain
values. For example, the delay domain values with lower indices are
assigned to user data. Consequently, the higher-numbered (or
indexed) delay domain values are used for the non-user data (or
Guard Grid symbols). The method 12800 includes, at step 12840,
converting the OTFS frame to time-domain samples in a
non-cyclic-prefix manner. The method 12800 includes, at step 12850,
generating a transmission waveform for the OTFS signal comprising
the time-domain samples.
[0773] FIG. 129 is a flowchart showing operations performed in an
example method 12900 for wireless communication using an orthogonal
time frequency space (OTFS) signal comprising one or more OTFS
frames in a two-dimensional delay-Doppler domain grid. The method
12900 includes, at step 12910, receiving the OFTS signal comprising
time-domain samples.
[0774] The method 12900 includes, at step 12920, converting the
time-domain samples to an OTFS frame in a non-cyclic-prefix manner,
wherein resource elements of the OTFS frame are partitioned into a
first set and a second set that include resource elements along a
delay dimension of the two-dimensional delay-Doppler domain grid,
wherein the first set of resource elements are used for non-user
data symbols, and wherein the second set of resource elements are
used for user data symbols. The method 12900 includes, at step
12930, performing channel estimation or equalization based on the
first set of resource elements. In methods 12700, 12800 and 12900,
the delay dimension of the two-dimensional delay-Doppler domain
grid is used to allocate the corresponding resource elements of the
OTFS frame to a user. Some embodiments and techniques related to
methods 12700, 12800 and 12900 may be described using the following
clause-based description.
[0775] 1. A wireless transmission method, comprising:
[0776] generating a signal by concatenating orthogonal time
frequency space (OTFS) symbols in a CP-less (cyclic-prefix-less)
manner, wherein in each OTFS frame in a two-dimensional
delay-Doppler domain grid, for at least some Doppler domain values,
a split allocation scheme is used for assigning transmission
resources along delay dimension, wherein the split allocation
scheme includes allocating a first portion to user data symbols and
a second portion to non-user data symbols; and transmitting the
signal over a wireless channel.
[0777] 2. The method of clause 1, wherein each Doppler domain value
includes the split allocation.
[0778] 3. The method of clauses 1 or 2, wherein each Doppler domain
value comprises a same size of the second portion.
[0779] 4. The method of any of clauses 1 to 3, wherein the non-user
data symbols comprise zero valued symbols.
[0780] 5. The method of any of clauses 1 to 3, wherein the second
portion of the lowest numbered Doppler domain value comprises known
symbols, and wherein the second portion of the other Doppler domain
values comprise zero-valued symbols.
[0781] 6. The method of any of clauses 1 to 5, further
comprising:
[0782] transmitting information associated with the split
allocation.
[0783] 7. The method of any of clauses 1 to 5, wherein information
associated with the split allocation is communicated as part of
control channel signaling.
[0784] 8. The method of any of clauses 1 to 5, wherein information
associated with the split allocation is communicated using physical
characteristics of the OTFS signal.
[0785] 9. The method of clause 1, wherein the second portion
comprises zero non-user data symbols.
[0786] 10. A method for wireless communication using an orthogonal
time frequency space (OTFS) signal comprising one or more OTFS
frames in a two-dimensional delay-Doppler domain grid, the method
comprising: partitioning resource elements of an OTFS frame into a
first set and a second set that include resource elements along a
delay dimension of the two-dimensional delay-Doppler domain grid;
using the first set of resource elements for non-user data symbols;
using the second set of resource elements to user data symbols,
wherein the second set of resource elements comprises
lower-numbered delay domain values; converting the OTFS frame to
time-domain samples in a non-cyclic-prefix manner; and generating a
waveform for transmission the OTFS signal comprising the
time-domain samples.
[0787] 11. The method of clause 10, wherein the delay dimension of
the two-dimensional delay-Doppler domain grid is used to allocate
the corresponding resource elements of the OTFS frame to a
user.
[0788] 12. The method of clauses 10 or 11, further comprising:
transmitting information associated with the partitioning of the
resource elements of the OTFS frame.
[0789] 13. The method of clauses 10 or 11, wherein information
associated with the partitioning of the resource elements of the
OTFS frame is communicated as part of control channel
signaling.
[0790] 14. The method of clauses 10 or 11, wherein information
associated with the partitioning of the resource elements of the
OTFS frame is communicated using physical characteristics of the
OTFS signal.
[0791] 15. The method of any of clauses 10 to 14, wherein a
zero-valued symbol is assigned to each of the first set of resource
elements.
[0792] 16. The method of any of clauses 10 to 14, wherein known
symbols are assigned to the first set of resource elements.
[0793] 17. The method of any of clauses 10 to 14, wherein known
symbols are assigned to resource elements of the first set that
correspond to a lowest numbered Doppler domain value, and wherein
zero-valued symbols are assigned to other resource elements of the
first set.
[0794] 18. The method of clause 16, wherein the known symbols
comprise pre-defined cyclic prefix or data-dependent symbols.
[0795] 19. The method of any of clauses 10 to 18, wherein each of
the one or more OTFS frames is preceded by a plurality of initial
guard samples.
[0796] 20. A method for wireless communication using an orthogonal
time frequency space (OTFS) signal comprising one or more OTFS
frames in a two-dimensional delay-Doppler domain grid, the method
comprising: receiving the OFTS signal comprising time-domain
samples; converting the time-domain samples to an OTFS frame in a
non-cyclic-prefix manner, wherein resource elements of the OTFS
frame are partitioned into a first set and a second set that
include resource elements along a delay dimension of the
two-dimensional delay-Doppler domain grid, wherein the first set of
resource elements are used for non-user data symbols, wherein the
second set of resource elements are used for user data symbols, and
wherein the second set of resource elements comprises
lower-numbered delay domain values; and performing channel
estimation or equalization based on the first set of resource
elements.
[0797] 21. The method of clause 20, wherein the delay dimension of
the two-dimensional delay-Doppler domain grid is used to allocate
the corresponding resource elements of the OTFS frame to a
user.
[0798] 22. The method of clauses 20 or 21, further comprising:
receiving information associated with the partitioning of the
resource elements of the OTFS frame.
[0799] 23. The method of clauses 20 or 21, wherein information
associated with the partitioning of the resource elements of the
OTFS frame is inferred from control channel signaling.
[0800] 24. The method of clauses 20 or 21, wherein information
associated with the partitioning of the resource elements of the
OTFS frame is inferred from physical characteristics of the OTFS
signal.
[0801] 25. The method of any of clauses 20 to 24, wherein a
zero-valued symbol is assigned to each of the first set of resource
elements.
[0802] 26. The method of any of clauses 20 to 24, wherein known
symbols are assigned to the first set of resource elements.
[0803] 27. The method of any of clauses 20 to 24, wherein known
symbols are assigned to resource elements of the first set that
correspond to a lowest numbered Doppler domain value, and wherein
zero-valued symbols are assigned to other resource elements of the
first set.
[0804] 28. The method of clause 27, wherein the known symbols
comprise pre-defined cyclic prefix or data-dependent symbols.
[0805] FIG. 130 is a flowchart illustrating an example method 13000
for wireless communication using OTFS. The method 13000 includes,
at step 13010, generating a plurality of coded bits from a
plurality of data bits using a forward error correction (FEC)
coder.
[0806] The method 13000 includes, at step 13020, generating a
plurality of symbols from the plurality of coded bits using a
symbol mapper.
[0807] The method 13000 includes, at step 13030, generating a
time-domain signal based on an inverse Fast Fourier Transform
(IFFT) of the plurality of symbols, wherein the IFFT is computed in
a Doppler domain.
[0808] The method 13000 includes, at step 13040, generating the
OTFS signal based on time-interleaving the time-domain signal.
[0809] The method 13000 includes, at step 13050, generating a
transmission waveform of the OTFS signal.
[0810] Some embodiments and techniques related to method 13000 may
be described using the following clause-based description.
[0811] 1. A method for wireless communication using an orthogonal
time frequency space (OTFS) signal, comprising: generating a
plurality of coded bits from a plurality of data bits using a
forward error correction (FEC) coder; generating a plurality of
symbols from the plurality of coded bits using a symbol mapper;
generating a time-domain signal based on an inverse Fast Fourier
Transform (IFFT) of the plurality of symbols, wherein the IFFT is
computed in a Doppler domain; generating the OTFS signal based on
time-interleaving the time-domain signal; and generating a
transmission waveform of the OTFS signal.
[0812] 2. A method for wireless communication using an orthogonal
time frequency space (OTFS) signal, comprising: receiving the OTFS
signal; generating a time-domain signal based on
time-deinterleaving the OTFS signal; generating a plurality of
symbols based on an Fast Fourier Transform (FFT) of the time-domain
signal, wherein the FFT is computed in a delay domain; generating a
plurality of coded bits from the plurality of symbols using a
symbol demapper; and generating a plurality of data bits from the
plurality of coded bits using a forward error correction (FEC)
decoder.
[0813] 3. A method for wireless communication using an orthogonal
time frequency space (OTFS) signal, comprising: generating a
plurality of coded bits from a plurality of data bits using a
forward error correction (FEC) coder; generating a plurality of
symbols from the plurality of coded bits using a symbol mapper;
generating a symbol stream based on repeating the plurality of
symbols in a time-domain; generating a time-domain signal based on
phase modulating the symbol stream; generating the OTFS signal
based on time-interleaving the time-domain signal; and generating a
transmission waveform of the OTFS signal.
[0814] 4. A method for wireless communication using an orthogonal
time frequency space (OTFS) signal, comprising: receiving the OTFS
signal; generating a time-domain signal based on
time-deinterleaving the OTFS signal; generating a symbol stream
based on conjugate phase modulating the time-domain signal;
generating a plurality of symbols based periodization of the symbol
stream in a time-domain; generating a plurality of coded bits from
the plurality of symbols using a symbol demapper; and generating a
plurality of data bits from the plurality of coded bits using a
forward error correction (FEC) decoder.
[0815] 5. A method for wireless communication using an orthogonal
time frequency space (OTFS) signal, implemented at a base station,
the method comprising: receiving the OTFS signal; generating a
first signal in a time-frequency domain based on a Fast Fourier
Transform (FFT) of the OTFS signal; generating a second signal
based on removing at least one cyclic prefix from the first signal;
generating a channel estimate in the time-frequency domain based on
the second signal and a reference signal; generating a first
equalized signal in the time-frequency domain based on the channel
estimate and the second signal; generating a first symbol stream in
a delay-Doppler domain based on an inverse symplectic Fast Fourier
Transform (ISFFT) of the first equalized signal; generating a
plurality of coded bits from the third signal using a symbol
demapper; and generating a plurality of data bits from the
plurality of coded bits using a forward error correction (FEC)
decoder.
[0816] 6. The method of clause 5, further comprising: generating a
second symbol stream in the delay-Doppler domain from the plurality
of coded bits using a symbol mapper; generating a third signal in
the time-frequency domain based on a symplectic Fast Fourier
Transform (SFFT) of the second symbol stream; and generating a
second equalized signal in the time-frequency domain based on the
channel estimate and the third signal.
[0817] 7. A method for wireless communication using an orthogonal
time frequency space (OTFS) signal, implemented at a base station,
the method comprising: generating a plurality of coded bits from a
plurality of data bits using a forward error correction (FEC)
coder; generating a plurality of symbols from the plurality of
coded bits using a symbol mapper; generating a first symbol stream
based on a Tomlinson-Harashima Precoding (THP) lattice perturbation
of the plurality of symbols; generating a second symbol stream
based on a symplectic Fast Fourier Transform (SFFT) of the first
symbol stream; generating a third symbol stream based on MMSE
precoding the second symbol stream; generating a time-domain signal
based on an inverse Fast Fourier Transform (IFFT) of the third
symbol stream; generating the OTFS signal based on adding at least
one cyclic prefix to the time-domain signal; and generating a
transmission waveform of the OTFS signal.
[0818] 8. The method of clause 7, wherein generating the third
symbol stream is further based on an extrapolated channel estimate,
and wherein the extrapolated channel estimate is based on at least
one reference signal.
[0819] 9. The method of clause 8, further comprising:
[0820] generating a fourth symbol stream based on an inverse
symplectic Fast Fourier Transform (ISFFT) of the extrapolated
channel estimate, and wherein generating the first symbol stream is
further based on the fourth symbol stream.
[0821] 10. A method for wireless communication using an orthogonal
time frequency space (OTFS) signal, implemented at a base station,
the method comprising: receiving a plurality of uplink reference
signals via a plurality of antennas; compute precoding information
based on processing the plurality of uplink reference signals; and
precoding information bits based on the precoding information.
Here, the processing of the plurality of uplink reference signals
comprises: extracting an uplink orthogonal reference signal from
the plurality of uplink reference signals; computing second order
statistics associated with the uplink orthogonal reference signal;
generating a channel estimate based on the uplink orthogonal
reference signal and the computed second order statistics; and
computing a reciprocity adjustment based on the channel adjustment.
The precoding information is computed further based on the second
order statistics and the reciprocity adjustment.
[0822] FIG. 131 is a block diagram illustration of an example of a
wireless communication system 13100. The system 13100 may include
one or more transmitters/receivers. For example, a transmitter
located at a base station 13104 may transmit signals s(t) to a
receiver device 13102, where the received signal r(t) may be
affected by the wireless channel that includes air medium and may
also include moving or stationary interferers or scatterers such as
buildings, vegetation and vehicle. The receiver device 13102 may
also transmit signals to the base station 13104, which are not
explicitly shown in the drawing. The receiver device 13102 may be a
user equipment such as a smartphone, a tablet computer, a laptop,
or a non-mobile equipment such as a small cel base station or a
wireless access receiver, and so on. The various transmitter-side
techniques described in the present document may be implemented
using the transmission circuitry of a base station 13104 and/or the
receiver apparatus 13102. The various receiver-side techniques
described in the present document may be implemented using receiver
circuitry of the base station 13104 and/or the receiver apparatus
13102.
[0823] FIG. 132 is a block diagram representation of a
communication apparatus 13200. The apparatus may include a
processor 13202. The apparatus 13200 may include a memory 13204.
The apparatus 13200 may include transmission and/or reception
circuitry 13206. The processor 13202 may be configured to implement
a method described in the present document. The memory 13204 may be
configured to store data during the implementation of a method, or
may store processor-executable code that, when executed by the
processor 13202, causes the processor 13202 to implement a
technique described in the present document. The transceiver
circuitry 13206 may be configured to perform signal reception or
signal transmission processing.
[0824] The disclosed and other embodiments, modules and the
functional operations described in this document can be implemented
in digital electronic circuitry, or in computer software, firmware,
or hardware, including the structures disclosed in this document
and their structural equivalents, or in combinations of one or more
of them. The disclosed and other embodiments can be implemented as
one or more computer program products, i.e., one or more modules of
computer program instructions encoded on a computer readable medium
for execution by, or to control the operation of, data processing
apparatus. The computer readable medium can be a machine-readable
storage device, a machine-readable storage substrate, a memory
device, a composition of matter effecting a machine-readable
propagated signal, or a combination of one or more them. The term
"data processing apparatus" encompasses all apparatus, devices, and
machines for processing data, including by way of example a
programmable processor, a computer, or multiple processors or
computers. The apparatus can include, in addition to hardware, code
that creates an execution environment for the computer program in
question, e.g., code that constitutes processor firmware, a
protocol stack, a database management system, an operating system,
or a combination of one or more of them. A propagated signal is an
artificially generated signal, e.g., a machine-generated
electrical, optical, or electromagnetic signal, that is generated
to encode information for transmission to suitable receiver
apparatus.
[0825] A computer program (also known as a program, software,
software application, script, or code) can be written in any form
of programming language, including compiled or interpreted
languages, and it can be deployed in any form, including as a
standalone program or as a module, component, subroutine, or other
unit suitable for use in a computing environment. A computer
program does not necessarily correspond to a file in a file system.
A program can be stored in a portion of a file that holds other
programs or data (e.g., one or more scripts stored in a markup
language document), in a single file dedicated to the program in
question, or in multiple coordinated files (e.g., files that store
one or more modules, sub programs, or portions of code). A computer
program can be deployed to be executed on one computer or on
multiple computers that are located at one site or distributed
across multiple sites and interconnected by a communication
network.
[0826] The processes and logic flows described in this document can
be performed by one or more programmable processors executing one
or more computer programs to perform functions by operating on
input data and generating output. The processes and logic flows can
also be performed by, and apparatus can also be implemented as,
special purpose logic circuitry, e.g., an FPGA (field programmable
gate array) or an ASIC (application specific integrated
circuit).
[0827] Processors suitable for the execution of a computer program
include, by way of example, both general and special purpose
microprocessors, and any one or more processors of any kind of
digital computer. Generally, a processor will receive instructions
and data from a read only memory or a random access memory or both.
The essential elements of a computer are a processor for performing
instructions and one or more memory devices for storing
instructions and data. Generally, a computer will also include, or
be operatively coupled to receive data from or transfer data to, or
both, one or more mass storage devices for storing data, e.g.,
magnetic, magneto optical disks, or optical disks. However, a
computer need not have such devices. Computer readable media
suitable for storing computer program instructions and data include
all forms of non-volatile memory, media and memory devices,
including by way of example semiconductor memory devices, e.g.,
EPROM, EEPROM, and flash memory devices; magnetic disks, e.g.,
internal hard disks or removable disks; magneto optical disks; and
CD ROM and DVD-ROM disks. The processor and the memory can be
supplemented by, or incorporated in, special purpose logic
circuitry.
[0828] While this patent document contains many specifics, these
should not be construed as limitations on the scope of an invention
that is claimed or of what may be claimed, but rather as
descriptions of features specific to particular embodiments.
Certain features that are described in this document in the context
of separate embodiments can also be implemented in combination in a
single embodiment. Conversely, various features that are described
in the context of a single embodiment can also be implemented in
multiple embodiments separately or in any suitable sub-combination.
Moreover, although features may be described above as acting in
certain combinations and even initially claimed as such, one or
more features from a claimed combination can in some cases be
excised from the combination, and the claimed combination may be
directed to a sub-combination or a variation of a sub-combination.
Similarly, while operations are depicted in the drawings in a
particular order, this should not be understood as requiring that
such operations be performed in the particular order shown or in
sequential order, or that all illustrated operations be performed,
to achieve desirable results.
[0829] Only a few examples and implementations are disclosed.
Variations, modifications, and enhancements to the described
examples and implementations and other implementations can be made
based on what is disclosed.
* * * * *